Echo cancellation methods, electronic devices, storage media, and software products

Abstract

This application discloses an echo cancellation method, electronic device, storage medium, and program product. The echo cancellation method includes: determining an echo simulation signal based on a first input signal using a nonlinear model; the nonlinear model describing the nonlinear relationship between the echo simulation signal and the first input signal; and performing echo cancellation processing on a second input signal based on the echo simulation signal. This application introduces a nonlinear model to determine the echo simulation signal. The nonlinear model can accurately describe the complex nonlinear relationship between the echo simulation signal and the first input signal, thereby more accurately simulating the actual echo generation process, making the echo simulation signal closer to the real echo signal. Based on this, using the echo simulation signal to perform echo cancellation processing on the second input signal picked up by the microphone can more accurately eliminate echo components, improve communication quality, and provide users with a complete and clear voice communication experience.

Description

Technical Field

[0001] This application relates to the field of echo cancellation, and in particular to an echo cancellation method, electronic device, storage medium, and program product. Background Technology

[0002] In communication systems, especially in voice communication and audio processing, echo has always been a significant factor affecting communication quality. Echoes primarily arise when the sound played from the speaker is picked up again by the microphone, thus mixing into the original input signal. This causes both parties to hear repeated sounds, affecting the clarity and naturalness of the call, reducing communication efficiency and user experience.

[0003] Traditional echo cancellation methods estimate and eliminate echo components using techniques such as linear filtering. However, their echo cancellation effect is unsatisfactory, with noticeable echo residue, failing to meet the requirements of high-quality communication. Summary of the Invention

[0004] The purpose of this application is to provide an echo cancellation method, electronic device, storage medium, and program product to solve the problem that the prior art cannot accurately eliminate echoes.

[0005] In a first aspect, this application provides a method for echo cancellation, comprising:

[0006] The echo simulation signal is determined based on the first input signal using a nonlinear model; the nonlinear model is used to describe the nonlinear relationship between the echo simulation signal and the first input signal; the first input signal is the signal input to the loudspeaker;

[0007] The echo cancellation process is performed on the second input signal based on the echo simulation signal; the second input signal is the signal picked up by the microphone.

[0008] This application's embodiments introduce a nonlinear model to determine the echo simulation signal. The nonlinear model accurately describes the complex nonlinear relationship between the echo simulation signal and the first input signal, thus more accurately simulating the actual echo generation process and making the echo simulation signal closer to the real echo signal. Based on this, the echo simulation signal is used to perform echo cancellation processing on the second input signal picked up by the microphone, which can more accurately eliminate echo components. This effectively overcomes the problems of incomplete echo cancellation in traditional technologies, improves communication quality, and provides users with a complete and clear voice communication experience.

[0009] In some possible implementations, the nonlinear model includes an electrical model, a mechanical model, and an acoustic model; the electrical model is used to describe the relationship between the first input signal and the nonlinear parameters of the speaker's voice coil; the mechanical model is used to describe the relationship between the nonlinear parameters of the voice coil and the nonlinear parameters of the speaker's diaphragm; and the acoustic model is used to describe the relationship between the nonlinear parameters of the diaphragm and the echo simulation signal.

[0010] In the embodiments of this application, the nonlinear model includes an electrical model, a mechanical model, and an acoustic model that focus on the nonlinear characteristics of different physical levels of the loudspeaker. It comprehensively and systematically covers various complex nonlinear factors in the loudspeaker's operation process. Compared with a single model, it can more accurately capture every physical link in the generation of echo, thereby improving the accuracy of the echo simulation signal.

[0011] In some possible implementations, the echo analog signal is determined based on the first input signal using a nonlinear model, including:

[0012] The nonlinear parameters of the voice coil corresponding to the first input signal are determined based on the electrical model;

[0013] Determine the diaphragm nonlinear parameters corresponding to the voice coil nonlinear parameters based on a mechanical model;

[0014] The echo simulation signal corresponding to the nonlinear parameters of the diaphragm is determined based on the acoustic model.

[0015] In this embodiment, by sequentially applying electrical, mechanical, and acoustic models, echo-related feature parameters are extracted step-by-step and precisely from the first input signal, ultimately generating a high-precision echo simulation signal. Compared to a single model, this step-by-step processing method can more comprehensively consider the nonlinear characteristics of each component of the loudspeaker, thereby effectively improving the accuracy of echo simulation and providing data support for subsequent echo cancellation.

[0016] In some possible implementations, the nonlinear parameters of the speaker's voice coil include the voice coil magnetic force factor, and the nonlinear model also includes a first functional relationship, which describes the nonlinear relationship between the speaker's voice coil magnetic force factor and time and the speaker's voice coil displacement.

[0017] During loudspeaker sound production, as the voice coil moves within the magnetic circuit, the uneven distribution of the magnetic circuit causes a nonlinear change in the voice coil's magnetic force factor, resulting in nonlinear distortion of the sound emitted by the loudspeaker. In this embodiment, by incorporating the nonlinear relationship between the voice coil's magnetic force factor and its displacement and time into the model, the model can reflect the nonlinear characteristics of the voice coil's magnetic force factor. This allows for more accurate capture of the voice coil's actual behavior during dynamic operation, improving the accuracy of echo simulation and thus enhancing echo cancellation effectiveness, ensuring the clarity and naturalness of voice communication.

[0018] In some possible implementations, the nonlinear parameters of the loudspeaker diaphragm include diaphragm vibration stiffness, and the nonlinear model also includes a second functional relationship, which describes the nonlinear relationship between the loudspeaker diaphragm vibration stiffness and time, the loudspeaker diaphragm vibration angular frequency, and the voice coil displacement.

[0019] During loudspeaker sound production, the diaphragm's vibration stiffness changes nonlinearly with the vibration position, causing nonlinear distortion in the sound emitted by the loudspeaker. In this embodiment, by introducing a nonlinear relationship between the diaphragm's vibration stiffness and its angular frequency, voice coil displacement, and time into the nonlinear model, the complex dynamic behavior of the diaphragm in actual operation can be simulated more accurately. This allows for the capture of the nonlinear stiffness changes of the diaphragm under different vibration frequencies, voice coil displacements, and time conditions, thereby improving the accuracy of the echo simulation signal.

[0020] In some possible implementations, the nonlinear parameters of the loudspeaker diaphragm include diaphragm vibration damping, and the nonlinear model also includes a third function relationship, which describes the nonlinear relationship between the loudspeaker diaphragm vibration damping and time, the loudspeaker diaphragm vibration angular frequency, and the voice coil velocity.

[0021] During loudspeaker sound production, the diaphragm's vibration damping undergoes nonlinear changes due to the asymmetry of the air environment during its vertical vibration, resulting in nonlinear distortion of the sound emitted by the loudspeaker. In this embodiment, by introducing the nonlinear relationship between diaphragm vibration damping and diaphragm vibration angular frequency, voice coil velocity, and time into the nonlinear model, the energy dissipation characteristics of the diaphragm under different vibration states and time conditions can be captured more accurately, which helps to improve the accuracy of the echo simulation signal.

[0022] In some possible implementations, the nonlinear parameters of the loudspeaker diaphragm include the diaphragm vibration area, and the nonlinear model also includes a fourth function relationship, which is used to describe the nonlinear relationship between the loudspeaker diaphragm vibration area and the loudspeaker diaphragm vibration angular frequency and voice coil displacement.

[0023] During loudspeaker sound production, the effective vibrating area of ​​the loudspeaker diaphragm varies with its vertical vibration due to the asymmetrical distribution of the surrounds, resulting in inconsistent vibration areas and nonlinear distortion in the sound emitted by the loudspeaker. In this embodiment, by introducing a nonlinear relationship between the diaphragm's vibrating area, its angular frequency, and the voice coil displacement into the nonlinear model, the actual changes in the diaphragm's vibrating area under different vibration states can be simulated more accurately, thus improving the accuracy of the echo simulation signal.

[0024] In some possible implementations, the nonlinear parameters of the loudspeaker diaphragm include the front cavity stiffness, and the nonlinear model also includes a fifth function relationship, which is used to describe the nonlinear relationship between the front cavity stiffness of the loudspeaker and time, and the displacement of the loudspeaker's voice coil.

[0025] During loudspeaker sound production, the space in the loudspeaker's front cavity is largely occupied when the loudspeaker diaphragm moves upward and is restored when the diaphragm moves downward. This results in the front cavity's stiffness not being constant, causing nonlinear distortion in the sound emitted by the loudspeaker. In this embodiment, by introducing a nonlinear relationship between the front cavity stiffness and the voice coil displacement and time into the nonlinear model, the dynamic characteristics of the loudspeaker's front cavity can be simulated more accurately. This allows for the capture of changes in the front cavity stiffness under different voice coil displacement and time conditions, thereby improving the accuracy of the echo simulation signal.

[0026] In some possible implementations, the nonlinear parameters of the loudspeaker diaphragm include acoustic damping, and the nonlinear model also includes a sixth function relation, which is used to describe the nonlinear relationship between the loudspeaker's acoustic damping and time, and the loudspeaker's voice coil speed.

[0027] During loudspeaker sound production, the air in the front cavity encounters different pressures when it vibrates up and down as it is expelled and drawn in. This causes a nonlinear change in the acoustic damping of the front cavity, resulting in nonlinear distortion of the sound emitted by the loudspeaker. In this embodiment, by introducing a nonlinear relationship between acoustic damping and voice coil speed and time into the nonlinear model, the energy dissipation characteristics of the loudspeaker under different operating conditions can be simulated more accurately, thereby helping to improve the accuracy of the echo simulation signal.

[0028] In some possible implementations, echo cancellation processing is performed on the second input signal based on the echo analog signal, including:

[0029] The echo analog signal is subjected to adaptive filtering to obtain the filtered signal;

[0030] The filtered signal is inverted to obtain the first inverted signal;

[0031] The first inverted signal and the second input signal are added together to complete the echo cancellation process.

[0032] In this embodiment, adaptive filtering can dynamically adjust filtering parameters according to the characteristics of the actual echo signal, achieving more accurate echo analog signal processing and improving the accuracy and adaptability of echo cancellation. Phase inversion processing can generate a signal with the opposite phase to the echo signal. When added to the original echo signal, it can effectively cancel the echo, enhancing the efficiency and accuracy of echo cancellation.

[0033] In some possible implementations, echo cancellation processing is performed on the second input signal based on the echo analog signal, including:

[0034] The echo analog signal is inverted to obtain a second inverted signal;

[0035] The second inverted signal and the second input signal are added together to complete the echo cancellation process.

[0036] In this embodiment, the second inverted signal generated by the inversion process can be directly opposite in phase to the echo signal. When added together, it can effectively cancel the echo, improve the echo cancellation effect, and further improve the processing efficiency of echo cancellation, while reducing system load and latency.

[0037] Secondly, this application also provides an electronic device, comprising:

[0038] processor;

[0039] Memory;

[0040] The memory stores a computer program that, when executed, causes the electronic device to perform any of the methods described in the first aspect.

[0041] Thirdly, this application also provides a computer-readable storage medium including a stored program, wherein, when the program is running, it controls the device on which the computer-readable storage medium is located to execute the method of any one of the first aspects.

[0042] Fourthly, this application also provides a program product storing a program that, when run by an information processing device, causes the information processing device to execute the method described in any of the first aspects.

[0043] This application's embodiments introduce a nonlinear model to determine the echo simulation signal. The nonlinear model accurately describes the complex nonlinear relationship between the echo simulation signal and the first input signal, thus more accurately simulating the actual echo generation process and making the echo simulation signal closer to the real echo signal. Based on this, the echo simulation signal is used to perform echo cancellation processing on the second input signal picked up by the microphone, which can more accurately eliminate echo components. This effectively overcomes the problems of incomplete echo cancellation in traditional technologies, improves communication quality, and provides users with a complete and clear voice communication experience. Attached Figure Description

[0044] Figure 1 A schematic diagram of the top appearance of a mobile phone with a top microphone hole provided for an embodiment of this application;

[0045] Figure 2A schematic diagram of the top appearance of a mobile phone without a top microphone hole, provided for an embodiment of this application;

[0046] Figure 3 This is a schematic diagram of a mobile phone with a hole-free top, provided as an embodiment of this application.

[0047] Figure 4 A schematic diagram of the internal structure of a mobile phone in which the microphone and speaker share a narrow slit, provided as an embodiment of this application;

[0048] Figure 5 This is a schematic diagram of an echo cancellation method in the prior art;

[0049] Figure 6 This is a schematic diagram illustrating the principle of an echo cancellation method in the prior art;

[0050] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0051] Figure 8 A software structure block diagram of an electronic device provided in an embodiment of this application;

[0052] Figure 9 A schematic flowchart illustrating an echo cancellation method provided in an embodiment of this application;

[0053] Figure 10 A schematic diagram of an input signal echo cancellation process provided in an embodiment of this application;

[0054] Figure 11 for Figure 9 A flowchart illustrating step S01 of the provided echo cancellation method;

[0055] Figure 12 This is a schematic diagram of the structure of a first type of loudspeaker provided in an embodiment of this application;

[0056] Figure 13 This is a schematic diagram illustrating the relationship between a loudspeaker diaphragm and a voice coil structure, provided as an embodiment of this application.

[0057] Figure 14 This is a schematic diagram of the structure of the second type of loudspeaker provided in the embodiments of this application;

[0058] Figure 15 This is a schematic diagram of the structure of a loudspeaker diaphragm provided in an embodiment of this application;

[0059] Figure 16 This is a schematic diagram of the structure of the third type of loudspeaker provided in the embodiments of this application;

[0060] Figure 17A schematic diagram illustrating the air pressure change during the sound production process of a loudspeaker, provided as an embodiment of this application;

[0061] Figure 18 A schematic diagram of an equivalent circuit model of a loudspeaker provided in an embodiment of this application;

[0062] Figure 19 A comparative effect diagram of a residual time spectrum provided in an embodiment of this application;

[0063] Figure 20 This is a comparison diagram of a residual spectrum provided in an embodiment of this application. Detailed Implementation

[0064] To better understand the technical solution of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0065] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0066] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0067] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0068] The echo cancellation method provided in the embodiments of this application will be described below.

[0069] In communication systems, especially in voice communication and audio processing, echo has always been a significant factor affecting communication quality. Echoes primarily arise when the sound played from the speaker is picked up again by the microphone, thus mixing into the original input signal. This causes both parties to hear repeated sounds, affecting the clarity and naturalness of the call, reducing communication efficiency and user experience.

[0070] This section uses the iterative process of hardware design in a mobile phone acoustic system as an example for illustration:

[0071] See Figure 1This is a schematic diagram of the top appearance of a mobile phone with a top microphone hole, provided in an embodiment of this application. Figure 1 As shown, in order to ensure the sound pickup function, the phone has both a speaker hole and a microphone hole at the top. This design results in the holes at the top of the phone being asymmetrical, which affects the aesthetics of the top of the phone.

[0072] See Figure 2 This is a schematic diagram of the top appearance of a mobile phone without a top microphone hole, provided in an embodiment of this application. Figure 2 As shown, the phone has eliminated the top microphone hole, and by having the microphone and speaker share the same hole, the problem of asymmetrical holes at the top of the phone has been solved.

[0073] See Figure 3 This is a schematic diagram of a mobile phone with a hole-free top, provided in an embodiment of this application. Figure 3 As shown, the phone eliminates the top hole and instead uses a narrow slit above the screen to allow the speaker and microphone to share the same slit for sound output and pickup, thus solving the problem of the top hole affecting the phone's aesthetics.

[0074] Figures 1 to 3 The iterative process of hardware design in the illustrated mobile phone acoustic system demonstrates that aesthetics have gradually become a higher priority in mobile phone development. This design approach has led to new challenges in acoustic performance, particularly in echo suppression. Specifically, as speakers and microphones share apertures or even narrow slits, the microphone picks up relatively more echo energy, thus increasing the difficulty of echo suppression. Figure 1 In this design, the speaker's sound outlet and the pickup's sound pickup outlet are separate, but they are relatively close. The sound emitted by the speaker through the sound outlet is picked up by the pickup through the sound pickup outlet, resulting in an echo. In contrast,... Figure 2 and Figure 3 In this case, the microphone and the speaker share a hole or a narrow slit, which reduces the isolation between the speaker and the microphone, making it easier for the microphone to pick up the sound emitted by the speaker, further increasing the difficulty of echo suppression.

[0075] See Figure 4 ,for Figure 3 The diagram shows the internal acoustic system of a top-holeless mobile phone. Figure 4As shown, when the sound emitted by the speaker core is output through the front cavity sound outlet channel from the narrow slit in the exterior, due to the close distance between the front cavity sound outlet channel and the microphone pickup channel, some sound will be picked up by the microphone through the narrow slit in the exterior and the pickup channel, thus increasing the echo energy picked up by the microphone. Especially in a solution with a subwoofer built into a mobile phone, the microphone is located in the open rear cavity of the speaker. Some of the sound emitted by the speaker core can be directly picked up by the microphone through the rear cavity, further increasing the echo energy picked up by the microphone, which leads to a sharp increase in the difficulty of echo suppression.

[0076] To address the echo problem, in some possible implementations, echo cancellation is performed using an adaptive filter.

[0077] See Figure 5 This is a schematic diagram of an echo cancellation method provided in one embodiment of this application. Figure 5 As shown, when the speaker plays sound, it converts the received electrical signal (the far-end signal shown in the figure) into a sound signal (the speaker output signal shown in the figure) and outputs it. In order to ensure that the microphone only picks up the speech signal of the near-end speaker, an adaptive filter is used to eliminate the echo signal generated by the speaker in the input signal picked up by the microphone.

[0078] See Figure 6 ,for Figure 5 The diagram illustrates the principle of the echo cancellation method. Figure 6 As shown, the electrical signal input to the speaker is adaptively filtered by an adaptive filter, and the processed electrical signal is inverted by an inverter to obtain a signal that is inversely phase to the echo signal. This signal is then superimposed with the signal picked up by the microphone to eliminate the echo.

[0079] However, most of the aforementioned echo cancellation methods are based on linear models, presupposing a linear relationship between the echo signal and the signal input to the speaker. They use linear filters to estimate and cancel the echo components. However, in practical applications, echo generation is often accompanied by nonlinear distortion from the speaker. These nonlinear factors mean that the relationship between the actual echo signal and the input signal is not a simple linear one. Existing echo cancellation techniques based on linear models cannot accurately simulate and eliminate echoes when faced with this nonlinear distortion, resulting in unsatisfactory echo cancellation effects, noticeable echo residue, and an inability to meet the requirements of high-quality communication.

[0080] In view of this, embodiments of this application provide an echo cancellation method to solve the above-mentioned technical problems.

[0081] The following describes the electronic equipment to which the echo cancellation method provided in this application is applicable and the specific process of the method, in conjunction with the embodiments.

[0082] The echo cancellation method provided in this application can be applied to devices capable of screen touch control, such as mobile phones, tablets, personal computers (PCs), personal digital assistants (PDAs), smartwatches, netbooks, wearable electronic devices, augmented reality (AR) devices, virtual reality (VR) devices, in-vehicle devices, smart cars, smart speakers, robots, smart glasses, and smart TVs.

[0083] For example, see Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 7 As shown, the electronic device 100 may include a display screen 194, a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, antenna 1, antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, a headphone jack 170D, a sensor module 180, a motor 191, an indicator 192, a camera 193, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a touch sensor 180F.

[0084] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the electronic device 100. In other possible embodiments of this application, the electronic device 100 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0085] Display screen 194, also known as a display screen or screen, is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel may be an OLED display panel. In some possible embodiments, electronic device 100 may include one or N displays screens 194, where N is a positive integer greater than 1.

[0086] Processor 110 may include one or more processing units, such as application processor (AP), modem processor, controller, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU). These different processing units may be independent devices or integrated into one or more processors.

[0087] The controller can be the nerve center and command center of the electronic device 100. The controller can generate operation control signals according to the instruction opcode and timing signals to complete the control of fetching and executing instructions.

[0088] The processor 110 may also include a memory for storing instructions and data. In some possible embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from the memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0089] In some possible embodiments, the processor 110 may include one or more interfaces. Interfaces may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0090] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the electronic device 100. In other possible embodiments of this application, the electronic device 100 may also adopt different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0091] Internal memory 121 can be used to store executable program code, including instructions. Internal memory 121 may include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as network connection control functions), etc. The data storage area may store data created during the use of electronic device 100. In addition, internal memory 121 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, universal flash storage (UFS), etc. Processor 110 executes various functional applications and data processing of electronic device 100 by running instructions stored in internal memory 121 and / or instructions stored in memory located in the processor.

[0092] Electronic device 100 can implement audio functions, such as music playback and recording, through audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, and application processor.

[0093] The audio module 170 is used to convert digital audio information into analog audio signals for output, and also to convert analog audio input into digital audio signals. The audio module 170 can also be used for encoding and decoding audio signals. In some possible embodiments, the audio module 170 may be located in the processor 110, or some functional modules of the audio module 170 may be located in the processor 110.

[0094] The speaker 170A, also known as a "loudspeaker," is used to convert audio electrical signals into sound signals. The electronic device 100 can listen to music or make hands-free calls through the speaker 170A.

[0095] The receiver 170B, also known as the "earpiece," is used to convert audio electrical signals into sound signals. When the electronic device 100 answers a telephone call or voice message, the receiver 170B can be brought close to the ear to listen to the voice.

[0096] Microphone 170C, also known as a "microphone" or "voice transducer," is used to convert sound signals into electrical signals. When making a phone call or sending a voice message, the user can speak by bringing their mouth close to microphone 170C, inputting the sound signal into microphone 170C. Electronic device 100 may have at least one microphone 170C. In some other possible embodiments, electronic device 100 may have two microphones 170C, which, in addition to collecting sound signals, can also perform noise reduction. In other possible embodiments, electronic device 100 may also have three, four, or more microphones 170C, which can collect sound signals, reduce noise, identify the sound source, and perform directional recording, etc.

[0097] The 170D headphone jack is used to connect wired headphones. The 170D headphone jack can be a USB 130 interface or a 3.5mm Open Mobile Terminal Platform (OMTP) standard interface, a CTIA (Cellular Telecommunications Industry Association of the USA) standard interface.

[0098] See Figure 8 This is a software structure block diagram of an electronic device provided in an embodiment of this application. The software system of the electronic device 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture. This embodiment of the application uses the layered architecture Android system as an example to illustrate the software structure of the electronic device 100. The layered architecture divides the software into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. Figure 8 As shown in the embodiments of this application, the Android system includes, from top to bottom, the application layer, the framework layer, the hardware abstraction layer, and the kernel layer.

[0099] The application layer (App) may include a series of application packages. For example, these application packages may include applications such as gallery, file manager, charts, calendar, map, favorites, messaging, shopping, notes, and contacts. In this embodiment, the applications also include communication applications such as telephone, video conferencing, and voice conferencing. The communication application is used to determine the echo simulation signal based on a first input signal using a nonlinear model during communication; the nonlinear model describes the nonlinear relationship between the echo simulation signal and the first input signal; the first input signal is the signal input to the speaker; echo cancellation processing is performed on the second input signal based on the echo simulation signal; the second input signal is the signal picked up by the microphone.

[0100] The Framework (FWK) layer provides the application programming interface (API) and programming framework for applications in the application layer, including some predefined functions. Figure 2 In this application framework layer, a window manager, content provider, view system, phone manager, and resource manager can be included. The window manager manages window programs. It can obtain the screen size, determine the presence of a status bar, lock the screen, and capture the screen. The content provider stores and retrieves data, making this data accessible to the application. This data can include video, images, audio, made and received phone calls, browsing history and bookmarks, and a phone book. The view system includes visual controls, such as controls for displaying text and images. The view system can be used to build the application. The display interface can consist of one or more views. The phone manager provides communication functionality for the electronic device 100, such as managing call status (including connection and disconnection). The resource manager provides various resources for the application, such as localized strings, icons, images, layout files, audio files, etc.

[0101] The Hardware Abstraction Layer (HAL) is an interface layer located between the operating system kernel and the hardware circuitry, designed to abstract the hardware. It hides the hardware interface details of a specific platform, providing the operating system with a virtual hardware platform that is hardware-independent and portable across multiple platforms. For example, the HAL can provide virtual hardware for one or more audio processors, i.e., audio processing modules, capable of acquiring and processing audio data from underlying microphones and speakers. In some embodiments provided in this application, the HAL can use the audio processing module to determine an echo analog signal based on a first input signal using a nonlinear model, and then perform echo cancellation processing on a second input signal acquired from the hardware based on the echo analog signal, thereby supporting the efficient operation and functional implementation of communication applications.

[0102] The kernel layer is the layer between hardware and software. In some embodiments provided in this application, the kernel layer may include a microphone driver, an audio processor driver, and a speaker driver, etc. The speaker driver is used to drive the speaker to convert the received electrical signal (first input signal) into a sound signal. The microphone driver is used to drive the microphone to pick up a second input signal under different environments.

[0103] For ease of understanding, the following embodiments of this application will be described using the following methods: Figure 7 and Figure 8 Taking the electronic device with the structure shown as an example, and in conjunction with the accompanying drawings and application scenarios, the echo cancellation method provided in this application embodiment will be specifically described.

[0104] See Figure 9 This is a flowchart illustrating an echo cancellation method provided in an embodiment of this application. It can be understood that... Figure 9 The timing of the steps in the echo cancellation method described here is merely an example and does not impose any restrictions on the order of action execution. For example... Figure 9 As shown, applied to electronic devices, the main steps of the echo cancellation method provided in this application embodiment include:

[0105] S01: Determine the echo simulation signal based on the first input signal using a nonlinear model.

[0106] The nonlinear model is used to describe the nonlinear relationship between the echo simulation signal and the first input signal; the first input signal is the signal input to the loudspeaker.

[0107] In this embodiment, the nonlinear model is a mathematical model that can more accurately describe the complex nonlinear relationship between the first input signal to the loudspeaker and the generated echo simulation signal. Compared with the traditional linear model, the nonlinear model is no longer limited to a simple linear function, but fully considers the nonlinear distortion of the signal caused by the nonlinear characteristics of the loudspeaker itself. Through the nonlinear model, an echo simulation signal that is closer to the actual echo signal can be simulated more accurately, thus providing a more reliable basis for subsequent echo cancellation processing.

[0108] S02: Perform echo cancellation processing on the second input signal based on the echo simulation signal.

[0109] In this embodiment, the second input signal is the signal picked up by the microphone, which includes the user's voice and interference components such as echoes. The echo simulation signal is generated based on the first input signal using a nonlinear model to approximate the actual echo. Echo cancellation processing refers to separating the actual echo signal from the second input signal based on the echo simulation signal, thereby leaving a relatively pure user voice signal to improve the quality of voice communication and thus enhance the user experience.

[0110] The specific implementation of step S02 can be referred to the embodiments shown in subsequent steps S21 to S23 and steps S31 to S32, which will not be repeated here.

[0111] Based on the above technical solution, this application embodiment introduces a nonlinear model to determine the echo simulation signal. The nonlinear model can accurately describe the complex nonlinear relationship between the echo simulation signal and the first input signal, thereby more accurately simulating the actual echo generation process and making the echo simulation signal closer to the real echo signal. On this basis, using this echo simulation signal to perform echo cancellation processing on the second input signal picked up by the microphone can more accurately eliminate echo components, effectively overcoming the problems of incomplete echo cancellation in traditional technologies, improving communication quality, and providing users with a complete and clear voice communication experience.

[0112] See Figure 10 This is a schematic diagram of an input signal echo cancellation process provided in an embodiment of this application. Figure 10 As shown, in some embodiments provided in this application, a nonlinear model is used to determine an echo simulation signal based on a first input signal, and the echo simulation signal is used to perform echo cancellation processing on the second input signal picked up by the microphone, thereby eliminating the echo signal from the output signal and improving the quality of voice communication.

[0113] Based on the above embodiments, in some possible embodiments, to effectively improve the accuracy of echo simulation and thus the accuracy of echo cancellation, more accurate echo simulation signals can be generated through multiple related nonlinear models at different physical levels. That is, the nonlinear models can include electrical models, mechanical models, and acoustic models, wherein:

[0114] 1) The electrical model is used to describe the relationship between the first input signal and the nonlinear parameters of the speaker's voice coil.

[0115] When a loudspeaker operates, the first input signal (usually an electrical signal) is converted into an output sound signal. The loudspeaker's voice coil plays a crucial role in this conversion process, but its actual behavior is not perfectly linear. Therefore, in this embodiment, the electrical model is a mathematical model used to characterize the quantitative relationship between the first input signal and the nonlinear parameters of the loudspeaker's voice coil. It describes how the input electrical signal affects the behavior of the voice coil through the loudspeaker's electrical characteristics (such as impedance, inductance, and other nonlinear parameters), including the current and voltage waveforms in the voice coil and the distortion caused by nonlinear factors. This enables the system to determine the nonlinear parameters of the voice coil under different input signal conditions, thus laying the foundation for more accurate subsequent simulation of echo signals.

[0116] In some possible implementations, establishing the electrical model requires comprehensive measurement and analysis of the loudspeaker's electrical characteristics. This includes measuring the changes in parameters such as impedance and inductance of the loudspeaker under input signals of different frequencies and amplitudes, as well as the current and voltage waveforms in the voice coil. Using this experimental data, circuit analysis theory and nonlinear system modeling methods, such as polynomial models and Volterra series, can be applied to fit the relationship between the input signal and the nonlinear parameters of the voice coil.

[0117] 2) The mechanical model is used to describe the relationship between the nonlinear parameters of the voice coil and the nonlinear parameters of the speaker diaphragm.

[0118] In this embodiment, during loudspeaker operation, there is a close mechanical relationship between the movement of the voice coil and the vibration of the diaphragm. The mechanical model is a mathematical model used to accurately describe the interaction between the nonlinear parameters of the voice coil and the nonlinear parameters of the diaphragm. It encompasses the mechanical connection characteristics between the voice coil and the diaphragm, the force transmission and conversion process, and the nonlinear effects caused by factors such as material properties and geometry. The mechanical model accurately reflects how the movement of the voice coil affects the vibration state of the diaphragm through complex mechanical relationships, thus providing a crucial mechanical basis for more realistically simulating the acoustic output of the loudspeaker.

[0119] In some possible implementations, establishing a mechanical model requires detailed mechanical property testing of the speaker's voice coil and diaphragm. This includes measuring the voice coil's mechanical response (e.g., displacement, velocity, acceleration) under different currents and frequencies, as well as the changes in the diaphragm's mechanical parameters under different vibration modes. For example, specialized equipment such as laser vibrometers and dynamic mechanical analyzers can be used to acquire high-precision data. Then, combined with the experimental data, numerical modeling methods (such as finite element analysis and nonlinear regression) are used to construct the mechanical model. During model building, factors such as the connection stiffness between the voice coil and diaphragm, and nonlinear damping need to be considered, and the model parameters need to be continuously adjusted to match the model's output with the actual test results.

[0120] 3) The acoustic model is used to describe the relationship between the nonlinear parameters of the diaphragm and the echo simulation signal.

[0121] As a key component of a loudspeaker, the diaphragm's nonlinear vibration characteristics play a decisive role in the quality and characteristics of the output sound. However, traditional echo simulation methods often simplify this complex acoustic process, neglecting the subtle influence of diaphragm nonlinear parameters on sound wave morphology, leading to discrepancies between the simulated echo signal and the actual echo. Therefore, in this embodiment, the acoustic model transforms the complex nonlinear vibration characteristics of the diaphragm into quantifiable acoustic parameters, thereby accurately describing how these acoustic parameters change with the nonlinear vibration of the diaphragm, ultimately generating an echo simulation signal. It comprehensively considers the influence of factors such as diaphragm material properties, shape, vibration mode, and the surrounding acoustic environment on sound propagation, thus establishing a bridge between diaphragm nonlinear vibration and echo signals, enabling accurate prediction of echo signal characteristics based on the diaphragm's physical behavior.

[0122] In some possible implementations, the construction of the acoustic model requires comprehensive and accurate measurements of the acoustic characteristics of the loudspeaker diaphragm. This includes measuring acoustic parameters such as sound pressure distribution and directivity characteristics on the diaphragm surface under different vibration frequencies, amplitudes, and phases. For example, sophisticated acoustic measurement equipment, such as octave band analyzers and sound intensity probes, combined with a professional acoustic laboratory environment, can be used to acquire high-quality data. Then, based on linear acoustic theory and nonlinear acoustic principles, and combined with the physical structure and material properties of the diaphragm, numerical modeling methods are used to establish the acoustic model. During the model construction process, the nonlinear vibration equation of the diaphragm needs to be coupled with the sound wave propagation equation, and the model parameters need to be continuously adjusted to ensure that the model output matches the actual measured acoustic data.

[0123] Based on the above technical solutions, the nonlinear models in the embodiments of this application may include electrical models, mechanical models and acoustic models that focus on the nonlinear characteristics of different physical levels of the loudspeaker. They comprehensively and systematically cover all kinds of complex nonlinear factors in the loudspeaker's working process. Compared with a single model, they can more accurately capture every physical link in the generation of echo, thereby improving the accuracy of the echo simulation signal.

[0124] Based on the above embodiments, in some possible embodiments, see [link to relevant documentation]. Figure 11 ,for Figure 9 A schematic diagram illustrating the implementation flow of step S01 in a provided echo cancellation method. For example... Figure 11 As shown, step S01, which mentions using a nonlinear model to determine the echo simulation signal based on the first input signal, may specifically include the following steps:

[0125] S11: Determine the nonlinear parameters of the voice coil corresponding to the first input signal based on the electrical model.

[0126] In this embodiment of the application, by using an electrical model to establish a relationship between the electrical signal input to the loudspeaker (i.e. the first input signal) and the nonlinear parameters of the loudspeaker voice coil, the corresponding nonlinear parameters of the voice coil can be calculated based on the first input signal, laying the foundation for subsequent analysis of voice coil motion and diaphragm vibration.

[0127] The electrical characteristics of a loudspeaker's voice coil are not linearly constant during operation. For example, when the input signal amplitude is large, the inductance and resistance of the voice coil may change nonlinearly due to factors such as temperature variations and magnetic field saturation. Traditional linear models often fail to accurately capture these changes, leading to inaccurate predictions of the voice coil's behavior. By determining the nonlinear parameters of the voice coil corresponding to the first input signal based on an electrical model, the state of the voice coil under actual operating conditions can be more realistically reflected, thus improving the accuracy of the final echo simulation signal.

[0128] In some embodiments, circuit analysis software or mathematical modeling tools can be used to fit the parameters of an electrical model based on the measured loudspeaker parameters, forming a mathematical expression that describes the relationship between the input signal and the voice coil nonlinear parameters. When the first input signal enters the system, the corresponding voice coil nonlinear parameters can be calculated by substituting the signal characteristics (such as frequency, amplitude, etc.) into the electrical model. For example, a microprocessor can be used to run a pre-established electrical model algorithm to process the input signal in real time, obtaining parameters such as the nonlinear inductance and resistance values ​​of the voice coil, providing accurate electrical input for subsequent mechanical and acoustic analysis.

[0129] S12: Determine the diaphragm nonlinear parameters corresponding to the voice coil nonlinear parameters based on the mechanical model.

[0130] In this embodiment, the motion of the voice coil and the vibration of the diaphragm are closely linked through a mechanical mechanism, but this connection is affected by various nonlinear factors. By utilizing a predetermined mechanical model, known voice coil nonlinear parameters can be transformed into corresponding diaphragm nonlinear parameters, expressing the nonlinear characteristics generated by the diaphragm under voice coil drive, and providing a crucial mechanical basis for accurately simulating the sound signal emitted by the loudspeaker.

[0131] The vibration of the diaphragm is not only directly driven by the voice coil, but also exhibits complex nonlinear behavior due to its material properties, shape, and mounting method. Traditional simplified models often assume an ideal linear transmission relationship between the voice coil and the diaphragm, ignoring these nonlinear factors, thus leading to inaccurate predictions of the diaphragm's vibration state. By determining the diaphragm's nonlinear parameters corresponding to the voice coil's nonlinear parameters based on a mechanical model, the shortcomings of traditional models can be overcome, and the mechanical transmission process inside the loudspeaker can be reflected more realistically.

[0132] S13: Determine the echo simulation signal corresponding to the nonlinear parameters of the diaphragm based on the acoustic model.

[0133] In this embodiment, the sound signal is generated based on the vibration of the diaphragm. By using a predetermined acoustic model, the known nonlinear parameters of the diaphragm can be converted into corresponding echo simulation signals. This process simulates the influence of the nonlinear characteristics of the diaphragm on the sound signal generated by the loudspeaker, and can more realistically reflect the echo characteristics in the actual acoustic environment.

[0134] Based on the above technical solution, this embodiment of the application sequentially applies electrical, mechanical, and acoustic models to gradually and accurately extract echo-related feature parameters from the first input signal, ultimately generating a high-precision echo simulation signal. Compared to a single model, this step-by-step processing method can more comprehensively consider the nonlinear characteristics of each component of the loudspeaker, thereby effectively improving the accuracy of echo simulation and providing a more reliable basis for subsequent echo cancellation.

[0135] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the speaker's voice coil may include the voice coil magnetic force factor, and the nonlinear model may also include a first functional relationship, which is used to describe the nonlinear relationship between the speaker's voice coil magnetic force factor and time and the speaker's voice coil displacement.

[0136] See Figure 12 This is a schematic diagram of the structure of the first loudspeaker provided in an embodiment of this application. This is the voice coil displacement.

[0137] For the stroke of the voice coil, The thickness of the magnetically conductive upper plate.

[0138] like Figure 12 As shown, during the sound production process of a loudspeaker, when a current I flows through the voice coil in the magnetic gap with magnetic field strength B, the voice coil will move in the magnetic field due to the electromagnetic force F=BLI (where L is the length of the voice coil wire). However, the distribution of the magnetic circuit in the loudspeaker's magnetic field is not uniform; the closer to the magnetic pole, the denser the magnetic circuit, and the farther away from the magnetic pole, the sparser the magnetic circuit. This results in the voice coil experiencing different magnitudes of magnetic force at different positions.

[0139] The voice coil flux factor is the product of the magnetic field strength and the length of the voice coil conductor. It represents the magnitude of the electromagnetic force experienced by the voice coil in a magnetic field under a unit current; that is, the voice coil flux factor is BL. Due to the uneven distribution of the magnetic circuit in the loudspeaker's magnetic field, the voice coil flux factor BL is not a fixed value when the voice coil is in different positions. Instead, it changes nonlinearly with the movement of the voice coil, causing nonlinear distortion in the sound emitted by the loudspeaker. This results in a difference between the loudspeaker echo picked up by the pickup and the simulated echo, leading to unsatisfactory echo cancellation.

[0140] To address this issue, this application incorporates a first functional relationship describing the nonlinear relationship between the voice coil magnetic force factor and voice coil displacement and time into the nonlinear model, enabling the nonlinear model to reflect the nonlinear characteristics of the voice coil magnetic force factor. The first functional relationship is a mathematical expression used to quantitatively describe how the voice coil magnetic force factor changes nonlinearly with changes in voice coil displacement and time. Specifically, when the voice coil vibrates in the loudspeaker, changes in its position (displacement) and the passage of time affect the force exerted by the magnetic field on the voice coil, thereby altering the voice coil magnetic force factor. For example, as the voice coil displacement increases, the magnetic force factor may exhibit a nonlinear increasing or decreasing trend due to changes in magnetic field strength. Simultaneously, the time factor may also introduce some dynamic nonlinear characteristics, such as delays or changes caused by material hysteresis. By establishing the first functional relationship, the complex behavior of the voice coil during actual operation can be simulated more accurately.

[0141] In some possible embodiments, the process of establishing the first functional relationship may include the following steps:

[0142] First, detailed experimental testing of the speaker's voice coil is required. The magnetic flux density of the voice coil is measured under different voice coil displacement and time conditions. For example, a laser displacement sensor can be used to measure the voice coil displacement, while a fluxmeter or Hall effect sensor is used to measure the magnetic field strength, thereby calculating the magnetic flux density.

[0143] Then, based on the experimental data, mathematical methods such as nonlinear regression analysis, neural network modeling, or polynomial fitting are used to construct a functional model that describes the relationship between the voice coil magnetic force factor and displacement and time. During the model construction process, the model parameters need to be continuously adjusted to ensure that the error between the model's output and the actual measurement data is minimized.

[0144] For example, the first functional relationship can be determined by polynomial fitting:

[0145]

[0146] in, For voice coil magnetic force factor, This is the voice coil displacement. For time, Let be the order of the polynomial.

[0147] In practical applications, when the displacement and time of the voice coil are known, the magnetic force factor of the voice coil can be calculated using this functional relationship, providing accurate input for subsequent nonlinear model calculations. For example, in a real-time audio processing system, a microprocessor can run this functional model to quickly calculate the change in the magnetic force factor based on the real-time displacement and time data of the voice coil, thereby achieving accurate simulation of the speaker's behavior.

[0148] Based on the above technical solution, this application embodiment incorporates the nonlinear relationship between the voice coil magnetic force factor and the voice coil displacement and time into the model, enabling the model to reflect the nonlinear characteristics of the voice coil magnetic force factor. This allows for more accurate capture of the actual behavior of the voice coil during dynamic operation, which helps improve the accuracy of echo simulation, thereby enhancing the echo cancellation effect and ensuring the clarity and naturalness of voice communication.

[0149] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the speaker diaphragm may include the diaphragm vibration stiffness, and the nonlinear model may also include a second functional relationship, which is used to describe the nonlinear relationship between the speaker diaphragm vibration stiffness and time, the speaker diaphragm vibration angular frequency, and the voice coil displacement.

[0150] The vibration stiffness of a diaphragm refers to its ability to resist deformation. Its physical essence is a comprehensive reflection of the material's elastic modulus and structural design, and it directly affects acoustic performance.

[0151] See Figure 13 This is a schematic diagram illustrating the relationship between a loudspeaker diaphragm and a voice coil structure, provided in an embodiment of this application. Where x represents the voice coil displacement, and F represents the force on the voice coil.

[0152] like Figure 13 As shown, during the sound production process of a loudspeaker, when the voice coil is energized and moves back and forth in a magnetic field, it causes the diaphragm to vibrate accordingly. However, when the diaphragm vibrates to its maximum displacement, it undergoes elastic deformation, making vibration more difficult; at this point, the diaphragm's vibration stiffness reaches its maximum. When the voice coil displacement is zero, the diaphragm does not undergo elastic deformation, vibration is relatively easy, and the diaphragm's vibration stiffness is at its minimum.

[0153] The diaphragm stiffness of a loudspeaker changes nonlinearly with the position of vibration, causing nonlinear distortion in the sound emitted by the loudspeaker. This results in a difference between the loudspeaker echo picked up by the pickup and the simulated echo, leading to an unsatisfactory echo cancellation effect.

[0154] To address this issue, embodiments of this application introduce a second functional relationship into the nonlinear model to describe the nonlinear relationship between diaphragm vibration stiffness and diaphragm vibration angular frequency, voice coil displacement, and time. This second functional relationship is a mathematical model used to quantitatively describe this dynamic relationship. For example, as the diaphragm vibration angular frequency increases, the diaphragm vibration stiffness may increase or decrease due to the nonlinear elastic properties of the material; an increase in voice coil displacement may also lead to changes in diaphragm vibration stiffness, as the voice coil displacement affects the diaphragm's tension and stress state. The time factor includes some dynamic changes, such as material relaxation or fatigue effects, which further affect the diaphragm vibration stiffness. By establishing the second functional relationship, the stiffness variation characteristics of the diaphragm during actual operation can be simulated more accurately.

[0155] In some possible embodiments, the process of establishing the second functional relationship may include the following steps:

[0156] First, a systematic experimental test was conducted on the speaker diaphragm. The diaphragm's vibration stiffness was measured under different diaphragm vibration angular frequencies, voice coil displacements, and time conditions. For example, a laser vibrometer could be used to measure the diaphragm's vibration displacement, combined with a dynamic mechanical analyzer to measure the diaphragm's stiffness changes. Simultaneously, the voice coil displacement and time information were recorded to ensure the completeness and accuracy of the data.

[0157] Then, based on the experimental data, mathematical methods such as nonlinear regression analysis, neural network modeling, or polynomial fitting are used to construct a functional model that can describe the relationship between diaphragm vibration stiffness and diaphragm vibration angular frequency, voice coil displacement, and time.

[0158] For example, the second functional relationship can be determined by polynomial fitting:

[0159]

[0160] in, For diaphragm vibration stiffness, The angular frequency of the diaphragm vibration. This is the voice coil displacement. For time, Let be the order of the polynomial.

[0161] In practical applications, when the diaphragm's vibration angular frequency, voice coil displacement, and time are known, the diaphragm's vibration stiffness can be calculated using the second functional relationship, providing accurate input for subsequent nonlinear model calculations.

[0162] Based on the above technical solution, the embodiments of this application introduce a nonlinear relationship between the diaphragm vibration stiffness and the diaphragm vibration angular frequency, voice coil displacement and time into the nonlinear model, which can more accurately simulate the complex dynamic behavior of the diaphragm in actual work, and thus capture the nonlinear stiffness change of the diaphragm under different vibration frequencies, voice coil displacement and time conditions, thereby improving the accuracy of the echo simulation signal.

[0163] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm may include diaphragm vibration damping, and the nonlinear model may also include a third function relationship, which is used to describe the nonlinear relationship between the loudspeaker diaphragm vibration damping and time, the loudspeaker diaphragm vibration angular frequency, and the voice coil speed.

[0164] The vibration damping of a diaphragm refers to the ability of the diaphragm to convert mechanical energy into heat energy due to internal friction and structural deformation during vibration. It is a key parameter for energy dissipation during the vibration of a loudspeaker diaphragm and affects the attenuation characteristics of the diaphragm vibration.

[0165] See Figure 14 This is a schematic diagram of the structure of the second type of loudspeaker provided in an embodiment of this application. Figure 14 As shown, during the sound production process of a loudspeaker, when the voice coil is energized and moves back and forth in a magnetic field, it causes the diaphragm to vibrate accordingly. However, when the diaphragm vibrates to its maximum displacement, it undergoes elastic deformation, making vibration more difficult; at this point, the diaphragm's vibration stiffness reaches its maximum. When the voice coil displacement is zero, the diaphragm does not undergo elastic deformation, vibration is relatively easy, and the diaphragm's vibration stiffness is at its minimum.

[0166] When the diaphragm of a loudspeaker vibrates up and down, the damping will change nonlinearly due to the asymmetry of the air environment during vibration. This causes nonlinear distortion in the sound emitted by the loudspeaker, which leads to a difference between the loudspeaker echo picked up by the pickup and the simulated echo, resulting in an unsatisfactory echo cancellation effect.

[0167] To address this issue, embodiments of this application introduce a third functional relationship into the nonlinear model. This third functional relationship is a mathematical model used to quantitatively describe the nonlinear relationship between diaphragm vibration damping and the speaker's diaphragm vibration angular frequency, voice coil velocity, and time. For example, as the diaphragm vibration angular frequency increases, the damping may increase due to the viscoelastic properties of the material; an increase in voice coil velocity may also alter the damping characteristics, as the voice coil velocity affects airflow and frictional losses around the diaphragm. The time factor may introduce dynamic changes, such as material relaxation effects or changes in environmental conditions, further affecting diaphragm vibration damping. By establishing the third functional relationship, the energy dissipation behavior of the diaphragm during actual operation can be simulated more accurately.

[0168] In some possible embodiments, the process of establishing the third functional relationship may include the following steps:

[0169] First, a systematic experimental test is conducted on the speaker diaphragm. Under different diaphragm vibration angular frequencies, voice coil velocities, and time conditions, the diaphragm's vibration damping is measured. For example, a laser vibrometer can be used to measure the diaphragm's vibration velocity and displacement, combined with a dynamic mechanics analyzer to measure the diaphragm's damping characteristics. Simultaneously, the voice coil's velocity and time information are recorded to ensure the completeness and accuracy of the data.

[0170] Then, based on the experimental data, mathematical methods such as nonlinear regression analysis, neural network modeling, or polynomial fitting are used to construct a functional model that can describe the relationship between diaphragm vibration damping and diaphragm vibration angular frequency, voice coil velocity, and time.

[0171] For example, the third function relationship can be determined by polynomial fitting:

[0172]

[0173] in, For diaphragm vibration damping, The angular frequency of the diaphragm vibration. For voice coil speed, For time, Let be the order of the polynomial.

[0174] In practical applications, when the diaphragm's vibration angular frequency, voice coil velocity, and time are known, the diaphragm's vibration damping can be calculated using the third function relationship, providing accurate input for subsequent nonlinear model calculations.

[0175] Based on the above technical solution, the embodiments of this application introduce a nonlinear relationship between diaphragm vibration damping and diaphragm vibration angular frequency, voice coil velocity and time in the nonlinear model, which can more accurately capture the energy dissipation characteristics of the diaphragm under different vibration states and time conditions, and help improve the accuracy of echo simulation signals.

[0176] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the speaker diaphragm may include the diaphragm vibration area, and the nonlinear model may also include a fourth function relationship, which is used to describe the nonlinear relationship between the speaker diaphragm vibration area and the speaker diaphragm vibration angular frequency and voice coil displacement.

[0177] The diaphragm vibrating area refers to the portion of the diaphragm that can vibrate freely and produce sound. This area determines the amount of sound pressure and frequency response the diaphragm can generate when subjected to airflow or other external forces.

[0178] See Figure 15This is a schematic diagram of a loudspeaker diaphragm provided in an embodiment of this application. Wherein, c1 is the diameter of the effective vibration surface of the diaphragm when it vibrates upwards, and c2 is the diameter of the effective vibration surface of the diaphragm when it vibrates downwards.

[0179] like Figure 15 As shown, the surround is a crucial component connecting the diaphragm and the speaker frame, providing necessary support and elasticity. However, the presence of the surround causes an asymmetrical distribution of vibrations when the diaphragm vibrates vertically, resulting in changes in the effective vibrating area of ​​the diaphragm depending on the direction of vibration. When the diaphragm moves downwards, the effective vibrating area increases, while when the diaphragm moves upwards, the effective vibrating area decreases.

[0180] During the sound production process of a loudspeaker, the effective vibration area of ​​the loudspeaker diaphragm vibrates up and down. Due to the asymmetrical distribution of the surround, the vibration area vibrates inconsistently with the up and down movement, resulting in nonlinear distortion of the sound emitted by the loudspeaker. This causes a difference between the loudspeaker echo picked up by the pickup and the simulated echo, leading to an unsatisfactory echo cancellation effect.

[0181] To address this issue, embodiments of this application introduce a fourth functional relationship into the nonlinear model. This fourth functional relationship is a mathematical model used to quantitatively describe the nonlinear relationship between the diaphragm vibration area, the diaphragm vibration angular frequency, and the voice coil displacement of the loudspeaker. For example, when the diaphragm vibration angular frequency increases, the diaphragm's vibration mode may change, leading to an increase or decrease in the vibration area; an increase in voice coil displacement may also cause a change in the diaphragm vibration area, as the voice coil displacement affects the diaphragm's tension and vibration range. By establishing the fourth functional relationship, the characteristics of the diaphragm's vibration area change during actual operation can be simulated more accurately.

[0182] In some possible embodiments, the process of establishing the fourth functional relationship may include the following steps:

[0183] First, a systematic experimental test was conducted on the speaker diaphragm. The vibrating area of ​​the diaphragm was measured under different diaphragm vibration angular frequencies and voice coil displacements. For example, laser scanning can be used to measure the diaphragm's vibration modes and displacement distribution, and image processing techniques can be used to calculate the diaphragm's vibrating area. Simultaneously, the diaphragm vibration angular frequency and voice coil displacement data were recorded to ensure data integrity and accuracy.

[0184] Then, based on the experimental data, mathematical methods such as nonlinear regression analysis, neural network modeling, or polynomial fitting are used to construct a functional model that can describe the relationship between the diaphragm vibration area, the diaphragm vibration angular frequency, and the voice coil displacement.

[0185] For example, the fourth function relationship can be determined by polynomial fitting:

[0186]

[0187] in, The area of ​​the diaphragm during vibration. The angular frequency of the diaphragm vibration. This is the voice coil displacement. Let be the order of the polynomial.

[0188] In practical applications, when the diaphragm's angular frequency and voice coil displacement are known, the diaphragm's vibration area can be calculated using the fourth function relationship, providing accurate input for subsequent nonlinear model calculations.

[0189] Based on the above technical solution, the embodiments of this application introduce a nonlinear relationship between the diaphragm vibration area, the diaphragm vibration angular frequency, and the voice coil displacement into the nonlinear model, which can more accurately simulate the actual vibration area change of the diaphragm under different vibration states, and help improve the accuracy of the echo simulation signal.

[0190] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm may include the front cavity stiffness, and the nonlinear model may also include a fifth function relationship, which is used to describe the nonlinear relationship between the front cavity stiffness of the loudspeaker and time and the voice coil displacement of the loudspeaker.

[0191] The front cavity stiffness of a loudspeaker is a physical quantity that describes the ability of the closed air cavity in front of the diaphragm to resist changes in volume. Essentially, it is the equivalent spring stiffness formed by air elasticity.

[0192] See Figure 16 This is a schematic diagram of the structure of the third type of loudspeaker provided in an embodiment of this application. Figure 16 As shown, during the sound production process of a loudspeaker, when the diaphragm moves upward, it compresses the air in the front cavity, resulting in a decrease in equivalent acoustic compliance (an increase in stiffness); when it moves downward, the volume of the front cavity increases, resulting in an increase in acoustic compliance (a decrease in stiffness). That is, the diaphragm vibration compresses the air in the front cavity to generate a reaction force, the intensity of which is inversely proportional to the instantaneous volume.

[0193] During the sound production process of a loudspeaker, the space in the front cavity of the loudspeaker is mostly occupied when the loudspeaker diaphragm moves upward and is restored when the diaphragm moves downward. This causes the stiffness of the front cavity of the loudspeaker to be non-constant, resulting in non-linear distortion of the sound emitted by the loudspeaker. This leads to a difference between the loudspeaker echo picked up by the pickup and the simulated echo, which in turn results in an unsatisfactory echo cancellation effect.

[0194] To address this issue, embodiments of this application introduce a fifth functional relationship into the nonlinear model. The fifth functional relationship is a mathematical model used to quantitatively describe the nonlinear relationship between the front cavity stiffness of the loudspeaker and the voice coil displacement and time. For example, when the voice coil displacement increases, the compression or expansion of the air in the front cavity causes a change in the front cavity stiffness; the time factor can introduce some dynamic changes, such as the viscosity or thermal effect of air, thereby further affecting the front cavity stiffness. By establishing the fifth functional relationship, the stiffness variation characteristics of the front cavity air during actual operation can be simulated more accurately.

[0195] In some possible embodiments, the process of establishing the fifth functional relationship may include the following steps:

[0196] First, a systematic experimental test was conducted on the front cavity of the loudspeaker. The stiffness of the front cavity was measured under different voice coil displacement and time conditions. For example, a pressure sensor could be used to measure the pressure change within the front cavity, and the stiffness could be calculated by combining this data with the diaphragm displacement data. Simultaneously, voice coil displacement and time information were recorded to ensure the completeness and accuracy of the data.

[0197] Then, based on the experimental data, mathematical methods such as nonlinear regression analysis, neural network modeling, or polynomial fitting are used to construct a functional model that can describe the relationship between the front cavity stiffness and the voice coil displacement and time.

[0198] For example, the fifth function relationship can be determined by polynomial fitting:

[0199]

[0200] in, For the stiffness of the anterior cavity, This is the voice coil displacement. For time, Let be the order of the polynomial.

[0201] In practical applications, when the voice coil displacement and time are known, the front cavity stiffness can be calculated using the fifth function relationship, providing accurate input for subsequent nonlinear model calculations.

[0202] Based on the above technical solution, the embodiments of this application introduce a nonlinear relationship between the front cavity stiffness and the voice coil displacement and time in the nonlinear model, which can more accurately simulate the dynamic characteristics of the speaker front cavity, thereby capturing the change of the front cavity stiffness under different voice coil displacement and time conditions, thus improving the accuracy of the echo simulation signal.

[0203] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm include acoustic damping, and the nonlinear model also includes a sixth function relationship, which is used to describe the nonlinear relationship between the acoustic damping of the loudspeaker and the voice coil speed and time of the loudspeaker.

[0204] Sound damping refers to the physical phenomenon in which a loudspeaker system, during sound propagation, converts mechanical vibration energy into heat energy or other forms of dissipation through internal friction or external resistance, thereby suppressing vibration amplitude and reducing noise.

[0205] See Figure 17 This is a schematic diagram illustrating the air pressure change during the sound production process of a loudspeaker, provided in an embodiment of this application. Figure 17 As shown, during the sound production process of a loudspeaker, when the diaphragm vibrates upward (compressing the air in the front cavity), the air must overcome the higher ambient air pressure to be expelled; when it vibrates downward (expanding the front cavity), air is drawn in, forming a negative pressure zone. This pressure gradient difference causes the airflow resistance to exhibit a non-linear difference in the expulsion and intake directions.

[0206] During the sound production process of a loudspeaker, when the loudspeaker diaphragm vibrates up and down, the air in the front cavity of the loudspeaker encounters different pressures when it is expelled outward and drawn inward. This causes a nonlinear change in the acoustic damping of the front cavity, resulting in nonlinear distortion of the sound emitted by the loudspeaker. This leads to a difference between the loudspeaker echo picked up by the pickup and the simulated echo, which in turn results in an unsatisfactory echo cancellation effect.

[0207] To address this issue, embodiments of this application introduce a sixth function relationship into the nonlinear model. The sixth function relationship is a mathematical model used to quantitatively describe the nonlinear relationship between the acoustic damping of a loudspeaker and the voice coil speed and time. For example, as the voice coil speed increases, the airflow resistance around the diaphragm increases, leading to increased acoustic damping; the time factor can introduce dynamic changes, such as the viscosity or thermal effects of air, further affecting acoustic damping. By establishing the sixth function relationship, the energy dissipation behavior of the diaphragm during actual operation can be simulated more accurately.

[0208] In some possible embodiments, the process of establishing the sixth functional relationship may include the following steps:

[0209] First, a systematic experimental test was conducted on the front cavity of the loudspeaker. Changes in acoustic damping were measured under different voice coil displacement and time conditions. For example, a laser vibrometer could be used to measure the diaphragm's vibration velocity and displacement, combined with a pressure sensor to measure the pressure changes of the air surrounding the diaphragm, to calculate the acoustic damping. Simultaneously, voice coil velocity and time information were recorded to ensure the completeness and accuracy of the data.

[0210] Then, based on the experimental data, mathematical methods such as nonlinear regression analysis, neural network modeling, or polynomial fitting are used to construct a functional model that can describe the relationship between acoustic damping and voice coil speed and time.

[0211] For example, the sixth function relationship can be determined by polynomial fitting:

[0212]

[0213] in, For acoustic damping, For voice coil speed, For time, Let be the order of the polynomial.

[0214] In practical applications, when the voice coil speed and time are known, the front cavity stiffness can be calculated using the sixth function relationship, providing accurate input for subsequent nonlinear model calculations.

[0215] Based on the above technical solution, the embodiments of this application introduce a nonlinear relationship between acoustic damping and voice coil speed and time into the nonlinear model, which can more accurately simulate the energy dissipation characteristics of the loudspeaker under different working conditions, thereby helping to improve the accuracy of the echo simulation signal.

[0216] Based on the above embodiments, to improve the determination speed of the echo simulation signal, simplify the multiphysics coupling analysis of the loudspeaker, and achieve efficient extraction of key parameters, in some possible embodiments, the electrical model, mechanical model, and acoustic model can be determined based on the equivalent circuit model. This equivalent circuit model can be the electroacoustic multiphysics model of the loudspeaker.

[0217] See Figure 18 This is a schematic diagram of an equivalent circuit model of a loudspeaker provided in an embodiment of this application.

[0218] like Figure 18 As shown, the first input signal may include voltage. and current ,inductance and resistance Used to simulate a voice coil. The voice coil nonlinear parameters may include the voice coil magnetic force factor. .

[0219] Based on this, the electrical model used to describe the relationship between the first input signal and the voice coil characteristic parameters of the loudspeaker can be specifically as follows:

[0220]

[0221] in, For voltage, To simulate an inductor for a voice coil, The angular frequency of the diaphragm vibration. This is the voice coil displacement. For current, For time, To simulate the voice coil resistance, This is the magnetic force factor of the voice coil.

[0222] like Figure 18 As shown, the nonlinear parameters of the loudspeaker diaphragm can include diaphragm vibration stiffness. diaphragm vibration damping and diaphragm vibration area .

[0223] Based on this, the mechanical model describing the relationship between the voice coil nonlinearity parameters and the speaker diaphragm nonlinearity parameters can be specifically as follows:

[0224]

[0225] in, For vibrational mass, For diaphragm vibration damping, For diaphragm vibration stiffness, The angular frequency of the diaphragm vibration. This is the voice coil displacement. For voice coil speed, For sound pressure, For current, For time, To simulate the voice coil resistance, For voice coil magnetic force factor, This represents the diaphragm's vibrating area.

[0226] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm may further include the front cavity stiffness. and acoustic damping .

[0227] Based on this, the acoustic model used to describe the relationship between the diaphragm's nonlinear parameters and the echo simulation signal can be specifically as follows:

[0228]

[0229] in, For volume velocity, The sound quality value. The angular frequency of the diaphragm vibration. This is the voice coil displacement. For acoustic damping, For the stiffness of the anterior cavity, For time, The area of ​​the diaphragm during vibration. This refers to sound pressure level.

[0230] Based on the above embodiments, in some possible embodiments, the process of determining the voice coil nonlinear parameters corresponding to the first input signal based on the electrical model, as mentioned in step S11, may specifically include:

[0231] Interlocking electrical model and the first functional relationship The voice coil displacement is determined by considering the voice coil magnetic force factor.

[0232] The process mentioned in step S12, determining the diaphragm nonlinear parameters corresponding to the voice coil nonlinear parameters based on the mechanical model, may specifically include:

[0233] Co-dynamic model and the second functional relationship Third functional relationship Fourth functional relationship The diaphragm vibration area is determined by considering the nonlinear parameters of the diaphragm.

[0234] The process of determining the echo simulation signal corresponding to the diaphragm nonlinear parameters based on the acoustic model, as mentioned in step S13, may specifically include:

[0235] Linked acoustic model and the fifth function relationship The sixth functional relationship The output sound pressure is determined by considering the nonlinear parameters of the diaphragm.

[0236] Based on the above technical solutions, this application embodiment uses an equivalent circuit model to abstract acoustic paths (such as speaker-microphone coupling) into circuit networks (such as impedance and transmission delay) in echo cancellation. This helps quantify the frequency response characteristics and phase delay of the echo path, thereby optimizing the parameter design of the adaptive filter and achieving accurate echo cancellation. For example, by equating speaker impedance and room reverberation to RLC elements, the echo attenuation effect of different frequency bands can be quickly simulated, improving the algorithm's convergence speed and system stability.

[0237] Based on the above embodiments, in some possible embodiments, to achieve more accurate echo analog signal processing and improve echo cancellation effect, echo cancellation can be achieved through adaptive filtering and phase inversion processing. That is, as mentioned in step S02, in response to the user's operation exceeding a preset number of times, a quick task prompt interface is displayed, which may specifically include the following steps:

[0238] S21: Perform adaptive filtering on the echo analog signal to obtain the filtered signal.

[0239] In voice communication and audio processing systems, the characteristics of echo signals and environmental conditions can change over time. For example, noise in the call environment, changes in the acoustic path, and the movement of the caller can all affect the characteristics of the echo signal. Traditional fixed filters, whose parameters cannot be adjusted in real time, struggle to cope with these changes, resulting in poor echo cancellation performance.

[0240] In this embodiment, adaptive filtering of the echo analog signal involves dynamically adjusting the filter parameters using an adaptive filtering algorithm to make the filter output as close as possible to the actual echo signal. The core of adaptive filtering lies in its ability to adjust the filter's weight coefficients in real time to minimize the error between the filtered signal and the actual echo signal. In echo cancellation applications, adaptive filters continuously learn the characteristics of the input signal, effectively adapting to the time-varying characteristics of the signal and environmental changes, thereby improving the accuracy and efficiency of echo cancellation.

[0241] S22: Invert the filtered signal to obtain the first inverted signal.

[0242] In this embodiment, inverting the filtered signal involves reversing its phase by 180 degrees to obtain a first inverted signal. This step is achieved by multiplying each sample value of the signal by -1. The inverted signal is symmetrical to the original filtered signal in waveform but has the opposite phase. For example, if the amplitude of the original filtered signal is positive at a certain moment, the amplitude of the inverted signal at that moment will be negative, and the amplitudes will be the same.

[0243] The purpose of phase inversion is to generate a signal with the opposite phase to the actual echo signal, so as to achieve echo cancellation in subsequent addition processing. When the inverted signal is added to the actual echo signal, they cancel each other out because they are out of phase and have the same amplitude, thus achieving the effect of eliminating the echo.

[0244] S23: Add the first inverted signal and the second input signal to complete the echo cancellation process.

[0245] In this embodiment, echo cancellation is achieved by adding a first inverted signal to a second input signal. The first inverted signal is a filtered signal that has undergone phase inversion processing, and its phase is opposite to that of the original echo signal. The second input signal is a signal picked up by a microphone, containing both the original speech signal and the echo signal. When these two signals are added, the inverted signal and the echo signal have opposite phases but the same amplitude, thus canceling each other out and ultimately resulting in a clean signal containing only the original speech signal.

[0246] Based on the above technical solutions, in this embodiment, adaptive filtering can dynamically adjust the filtering parameters according to the characteristics of the actual echo signal, achieving more accurate echo analog signal processing and improving the accuracy and adaptability of echo cancellation. Phase inversion processing can generate a signal with the opposite phase to the echo signal. When added to the original echo signal, it can effectively cancel the echo, enhancing the efficiency and accuracy of echo cancellation.

[0247] Based on the above embodiments, in some possible embodiments, to improve the processing efficiency of echo cancellation and reduce system load and latency, the echo analog signal can be directly inverted to obtain a second inverted signal, which is then added to the second input signal to achieve echo cancellation. That is, as mentioned in step S02, performing echo cancellation processing on the second input signal based on the echo analog signal can specifically be as follows:

[0248] S31: Invert the echo analog signal to obtain a second inverted signal.

[0249] In this embodiment, the echo analog signal is inverted by 180 degrees, generating a signal with the opposite phase to the original echo signal, i.e., a second inverted signal. This process is achieved by multiplying each sample value of the echo analog signal by -1, making the newly generated signal symmetrical to the original echo signal in waveform but with completely opposite phase. This embodiment eliminates the need for adaptive filtering of the echo analog signal, further improving the efficiency of echo cancellation and reducing system load and latency.

[0250] S32: Add the second inverted signal and the second input signal to complete the echo cancellation process.

[0251] In this embodiment, the second inverted signal is obtained by inverting the echo analog signal, and its phase is opposite to that of the echo signal. The second input signal contains the user's speech and the echo. When these two signals are added together, the echo components cancel each other out due to their opposite phase, and the final output signal mainly contains the user's speech.

[0252] Based on the above technical solution, the second inverted signal generated by the inversion process can be directly opposite in phase to the echo signal. When added together, it can effectively cancel the echo, improve the echo cancellation effect, and further improve the processing efficiency of echo cancellation, while reducing system load and latency.

[0253] See Figure 19 and Figure 20 , Figure 19 A comparative effect diagram of a residual time spectrum provided in an embodiment of this application; Figure 20 This is a comparison diagram of a residual spectrum provided in an embodiment of this application. Figure 19 As shown in (1), when the first input signal is used as a reference and the speaker nonlinearity factor is not included, the residual after linear echo cancellation is relatively large; as Figure 19 As shown in (2), when the echo simulation signal after considering the nonlinearity of the loudspeaker is used as a reference, the residual after linear echo cancellation is relatively small.

[0254] like Figure 20 As shown, the residual after linear echo cancellation using the analog echo signal considering speaker nonlinearity as a reference is significantly smaller than the residual after linear echo cancellation using the first input signal as a reference. In other words, from the perspective of residuals, the echo cancellation method provided in this application embodiment is more effective.

[0255] This application embodiment also provides an echo cancellation device, which may include:

[0256] The analog signal determination module is used to determine the echo analog signal based on the first input signal using a nonlinear model; the nonlinear model is used to describe the nonlinear relationship between the echo analog signal and the first input signal; the first input signal is the signal input to the loudspeaker;

[0257] The echo cancellation module is used to perform echo cancellation processing on the second input signal based on the echo analog signal; the second input signal is the signal picked up by the microphone.

[0258] Based on the above embodiments, in some possible embodiments, the nonlinear model includes an electrical model, a mechanical model, and an acoustic model; the electrical model is used to describe the relationship between the first input signal and the nonlinear parameters of the speaker's voice coil; the mechanical model is used to describe the relationship between the nonlinear parameters of the voice coil and the nonlinear parameters of the speaker's diaphragm; and the acoustic model is used to describe the relationship between the nonlinear parameters of the diaphragm and the echo simulation signal.

[0259] Based on the above embodiments, in some possible embodiments, the analog signal determination module can specifically be used for:

[0260] The nonlinear parameters of the voice coil corresponding to the first input signal are determined based on the electrical model;

[0261] Determine the diaphragm nonlinear parameters corresponding to the voice coil nonlinear parameters based on a mechanical model;

[0262] The echo simulation signal corresponding to the nonlinear parameters of the diaphragm is determined based on the acoustic model.

[0263] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the speaker's voice coil include the voice coil magnetic force factor, and the nonlinear model also includes a first functional relationship, which is used to describe the nonlinear relationship between the speaker's voice coil magnetic force factor and the speaker's voice coil displacement and time.

[0264] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the speaker diaphragm include the diaphragm vibration stiffness, and the nonlinear model also includes a second functional relationship, which is used to describe the nonlinear relationship between the speaker diaphragm vibration stiffness and the speaker diaphragm vibration angular frequency, voice coil displacement and time.

[0265] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm include diaphragm vibration damping, and the nonlinear model also includes a third function relationship, which is used to describe the nonlinear relationship between the loudspeaker diaphragm vibration damping and the loudspeaker diaphragm vibration angular frequency, voice coil velocity and time.

[0266] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the speaker diaphragm include the diaphragm vibration area, and the nonlinear model also includes a fourth functional relationship, which is used to describe the nonlinear relationship between the speaker diaphragm vibration area and the speaker diaphragm vibration angular frequency and voice coil displacement.

[0267] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm include the front cavity stiffness, and the nonlinear model also includes a fifth function relationship, which is used to describe the nonlinear relationship between the front cavity stiffness of the loudspeaker and the displacement and time of the loudspeaker's voice coil.

[0268] Based on the above embodiments, in some possible embodiments, the nonlinear parameters of the loudspeaker diaphragm include acoustic damping, and the nonlinear model also includes a sixth function relationship, which is used to describe the nonlinear relationship between the acoustic damping of the loudspeaker and the voice coil speed and time of the loudspeaker.

[0269] Based on the above embodiments, in some possible embodiments, the echo cancellation module may specifically be used for:

[0270] The echo analog signal is subjected to adaptive filtering to obtain the filtered signal;

[0271] The filtered signal is inverted to obtain the first inverted signal;

[0272] The first inverted signal and the second input signal are added together to complete the echo cancellation process.

[0273] Based on the above embodiments, in some possible embodiments, the echo cancellation module can specifically be used for:

[0274] The echo analog signal is inverted to obtain a second inverted signal;

[0275] The second inverted signal and the second input signal are added together to complete the echo cancellation process.

[0276] It should be understood that the term "module" in the embodiments of this application can be implemented in software and / or hardware, and is not specifically limited thereto. For example, a "module" can be a software program, a hardware circuit, or a combination of both that implements the above-described functions. Hardware circuits may include application-specific integrated circuits (ASICs), electronic circuits, processors (e.g., shared processors, proprietary processors, or group processors, etc.) and memory for executing one or more software or firmware programs, combined logic circuits, and / or other suitable components that support the described functions.

[0277] Therefore, the modules of the various examples described in the embodiments of this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0278] This application also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the various steps of the echo cancellation method of this application.

[0279] This application also provides a computer program product containing instructions that, when run on a computer or any at least one processor, cause the computer to perform the various steps of the echo cancellation method of this application.

[0280] This application also provides a chip, including a processor and a data interface. The processor reads instructions stored in the memory through the data interface to execute the corresponding operations and / or processes of the echo cancellation method provided in this application.

[0281] Optionally, the chip further includes a memory connected to the processor via a circuit or wire, the processor being used to read and execute computer programs stored in the memory. Further optionally, the chip includes a communication interface to which the processor is connected. The communication interface is used to receive data and / or information that needs to be processed, the processor obtaining the data and / or information from the communication interface and processing the data and / or information. The communication interface can be an input / output interface.

[0282] The memory can be read-only memory (ROM), other types of static storage devices that can store static information and instructions, random access memory (RAM), or other types of dynamic storage devices that can store information and instructions. It can also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices. Alternatively, it can be any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

[0283] In this embodiment, "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, or the existence of B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0284] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0285] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0286] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0287] The above description is merely a specific embodiment of this application. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. The protection scope of this application shall be determined by the scope of the claims.

Claims

1. A method for echo cancellation, characterized in that, include: The echo simulation signal is determined based on the first input signal using a nonlinear model; The nonlinear model is used to describe the nonlinear relationship between the echo analog signal and the first input signal; The first input signal is a signal input to the loudspeaker; the nonlinear model includes an electrical model, a mechanical model, and an acoustic model; the electrical model is used to describe the relationship between the first input signal and the nonlinear parameters of the loudspeaker's voice coil; The mechanical model is used to describe the relationship between the voice coil nonlinearity parameter and the diaphragm nonlinearity parameter of the loudspeaker; The acoustic model is used to describe the relationship between the diaphragm nonlinear parameters and the echo simulation signal; The nonlinear parameters of the loudspeaker's diaphragm include the diaphragm vibration area. The nonlinear model also includes a fourth functional relationship, which describes the nonlinear relationship between the loudspeaker's diaphragm vibration area and the loudspeaker's diaphragm vibration angular frequency and voice coil displacement. The nonlinear parameters of the loudspeaker's diaphragm include the front cavity stiffness. The nonlinear model also includes a fifth functional relationship, which describes the nonlinear relationship between the loudspeaker's front cavity stiffness and time, and the loudspeaker's voice coil displacement. The nonlinear parameters of the loudspeaker diaphragm include acoustic damping, and the nonlinear model also includes a sixth function relationship, which is used to describe the nonlinear relationship between the acoustic damping of the loudspeaker and time and the voice coil speed of the loudspeaker; The second input signal is subjected to echo cancellation processing based on the echo simulation signal; the second input signal is the signal picked up by the microphone.

2. The method according to claim 1, characterized in that, The method of determining the echo simulation signal based on the first input signal using a nonlinear model includes: The voice coil nonlinear parameters corresponding to the first input signal are determined based on the electrical model. Based on the mechanical model, determine the diaphragm nonlinear parameters corresponding to the voice coil nonlinear parameters; The echo simulation signal corresponding to the nonlinear parameters of the diaphragm is determined based on the acoustic model.

3. The method according to claim 1 or 2, characterized in that, The nonlinear parameters of the speaker's voice coil include the voice coil magnetic force factor, and the nonlinear model also includes a first functional relationship, which describes the nonlinear relationship between the speaker's voice coil magnetic force factor and time, and the speaker's voice coil displacement.

4. The method according to claim 1 or 2, characterized in that, The nonlinear parameters of the loudspeaker diaphragm include diaphragm vibration stiffness. The nonlinear model also includes a second functional relationship, which describes the nonlinear relationship between the loudspeaker diaphragm vibration stiffness and time, the loudspeaker diaphragm vibration angular frequency, and voice coil displacement.

5. The method according to claim 1 or 2, characterized in that, The nonlinear parameters of the loudspeaker diaphragm include diaphragm vibration damping. The nonlinear model also includes a third function relationship, which describes the nonlinear relationship between the loudspeaker diaphragm vibration damping and time, the loudspeaker diaphragm vibration angular frequency, and the voice coil velocity.

6. The method according to claim 1 or 2, characterized in that, The echo cancellation processing of the second input signal based on the echo analog signal includes: The echo analog signal is subjected to adaptive filtering to obtain a filtered signal; The filtered signal is inverted to obtain a first inverted signal; The first inverted signal and the second input signal are added together to complete the echo cancellation process.

7. The method according to claim 1 or 2, characterized in that, The echo cancellation processing of the second input signal based on the echo analog signal includes: The echo analog signal is inverted to obtain a second inverted signal; The second inverted signal and the second input signal are added together to complete the echo cancellation process.

8. An electronic device, characterized in that, include: processor; Memory; The memory stores a computer program that, when executed, causes the electronic device to perform the method described in any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method according to any one of claims 1-7.

10. A program product, characterized in that, The program product stores a program that, when run by an information processing device, causes the information processing device to perform the method as described in any one of claims 1-7.

Images