Adjusting method of intelligent loudspeaker box, intelligent equipment and storage medium

Abstract

The invention discloses an adjusting method of an intelligent sound box, intelligent equipment and a storage medium. Sound data of an environment where the intelligent sound box is located is collected, acoustic characteristic analysis is performed on the environment, acoustic parameters related to the intelligent sound box are automatically adjusted according to an acoustic analysis result, an acoustic model is formulated, and the intelligent sound box is adjusted according to the sound listening preference of a user. And formulating an acoustic model matched with the listening preference of the user. According to the invention, different listening environments can be automatically identified and adapted, the acoustic characteristics of the environments are analyzed in real time, and the frequency response and sound directivity of the sound box are automatically adjusted by applying a digital signal processing algorithm and a machine learning technology, so that personalized acoustic experience is provided for a user, and the overall sound quality effect is improved.

Description

Technical Field

[0001] The present invention relates to the fields of artificial intelligence and Internet technology, and in particular to an adjustment method for a smart speaker, a smart device, and a storage medium. Background Art

[0002] In the current field of audio equipment, although there are various types of speakers on the market, they often cannot be adaptively adjusted according to different listening environments. Existing speaker equipment cannot provide the best listening experience when encountering room acoustic problems such as echo and resonance. In addition, with the development of wireless communication technology, Bluetooth speakers are popular for their convenience, but the technology in acoustic tuning still needs to be improved. The current cutting-edge directions in the field include the application of digital signal processing, machine learning and other technologies in acoustic optimization. How to identify environmental changes in real time and accurately, and quickly adjust the speakers to adapt to new acoustic conditions, is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of the above-mentioned defects, the technical problem solved by the present invention is to provide a method for adjusting a smart speaker by integrating an advanced intelligent control system, which can automatically identify and adapt to different listening environments, analyze the acoustic characteristics of the environment in real time, and use digital signal processing algorithms and machine learning technology to automatically adjust the frequency response and sound directivity of the speaker, thereby providing users with a personalized acoustic experience and improving the overall sound quality.

[0004] A first aspect of the present invention provides a method for adjusting a smart speaker, the method comprising: S101: collecting environmental sound data of the smart speaker, and performing acoustic characteristic analysis on the environment.

[0005] S102: According to the acoustic analysis result, automatically adjust the acoustic parameters related to the smart speaker and formulate an acoustic model.

[0006] S103: In combination with the user's listening preference, an acoustic model matching the user's listening preference is formulated.

[0007] According to an embodiment of the present invention, the sound data includes: sound timbre data, sound frequency and sound amplitude.

[0008] According to an embodiment of the present invention, the acoustic characteristic analysis of the environment includes: the sound timbre data, sound frequency and sound amplitude are analyzed by a digital signal processor to identify acoustic parameters related to the sound data.

[0009] According to an embodiment of the present invention, the performing acoustic characteristic analysis on the environment further includes: detecting whether there are acoustic defects in the environment by adjusting the sound pressure level of the microphone, as shown in formula (1), Formula (1) in, Indicates the severity of the acoustic defect, represents the sound pressure level of the i-th microphone, Represents the average of the sound pressure level measurements from all microphones.

[0010] According to an embodiment of the present invention, automatically adjusting the acoustic parameters related to the smart speaker according to the acoustic analysis result includes: adjusting the gain value of each frequency band of the environment, as shown in formula (2), Formula (2) in, Indicates the frequency band that needs to be adjusted The sound pressure gain value is Indicates the first sound pressure gain value of the target frequency band, Indicates the second sound pressure gain value of the actual measured frequency band.

[0011] According to an embodiment of the present invention, the step of formulating an acoustic model matching the user's listening preference in combination with the user's listening preference in S103 includes: collecting the user's listening preference data.

[0012] The listening preference data is feature extracted as first listening preference data, and the first listening preference data is input into the acoustic model to obtain a listening preference acoustic model matching the user.

[0013] The second aspect of the present invention provides an intelligent device, including a transmitter, a receiver, a memory and a processor; the memory is used to store computer instructions; the processor is used to run the computer instructions stored in the memory to implement the above-mentioned intelligent speaker adjustment method.

[0014] The third aspect of the present invention provides a storage medium, comprising: a readable storage medium and computer instructions, wherein the computer instructions are stored in the readable storage medium; the computer instructions are used to implement the above-mentioned smart speaker adjustment method.

[0015] The beneficial effects provided by the present invention are as follows: by integrating an advanced intelligent control system, it can automatically identify and adapt to different listening environments, analyze the acoustic characteristics of the environment in real time, and use digital signal processing algorithms and machine learning technology to automatically adjust the frequency response and sound directivity of the speaker, thereby providing users with a personalized acoustic experience. While ensuring accuracy, the overall sound quality effect is also greatly improved.

[0016] At the same time, by increasing the attenuation of specific frequencies and reducing the reverberation effect, the speaker output is matched with the acoustic characteristics of the environment, achieving the optimization of sound quality following the environment, while bringing users a more immersive listening experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0018] Figure 1 This is a flow chart of the adjustment method of the smart speaker disclosed in an embodiment of the present invention.

[0019] The above drawings show clear embodiments of the present disclosure, which will be described in more detail below. These drawings and text descriptions are not intended to limit the scope of the present disclosure in any way, but to illustrate the concepts of the present disclosure to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0020] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0021] The present invention discloses an intelligent acoustic tuning Bluetooth speaker, which can automatically identify and adapt to different listening environments by integrating an advanced intelligent control system, analyze the acoustic characteristics of the environment in real time, and use digital signal processing algorithms and machine learning technology to automatically adjust the frequency response and sound directivity of the speaker, thereby providing users with a personalized acoustic experience and improving the overall sound quality.

[0022] Specifically, Figure 1 As shown, based on real-time monitoring of environmental acoustic characteristics, the built-in microphone collects environmental sound data and analyzes the room acoustic characteristics.

[0023] The smart speaker in the present invention is equipped with multiple high-sensitivity microphones, which are responsible for synchronously collecting sound signals from the surrounding environment. Real-time monitoring and evaluation of environmental acoustic characteristics are achieved through the following steps: First, S101: collect the sound data of the environment where the smart speaker is located, and analyze the acoustic characteristics of the environment. The microphone array comprehensively captures the ambient sound from all directions to ensure that the collected sound data fully reflects the acoustic characteristics of the listening space. The collected sound data includes timbre, frequency, amplitude, etc.

[0024] The collected sound data is analyzed for acoustic characteristics and fed into the built-in digital signal processor (DSP). The DSP uses a pre-trained machine learning model to analyze the sound signal and identify key acoustic parameters including reverberation time, frequency characteristics, and noise level.

[0025] The acoustic defect detection is performed on the sound data. The analysis process pays special attention to the standing waves and acoustic resonance problems in the room. The improvement method of this problem is to reduce the impact by adjusting the sound pressure level of the microphone. The algorithm is used to detect whether there are acoustic defects caused by the room geometry, as shown in formula (1).

[0026] Formula (1) in, Indicates the severity of the acoustic defect, represents the sound pressure level of the i-th microphone, Represents the average of the sound pressure level measurements from all microphones.

[0027] Taking a specific listening room as an example, after the user turns it on, the smart speaker automatically starts the microphone array to collect sound data. By analyzing the collected sound data, the DSP recognizes that the room reverberation time is 0.8 seconds and detects that there is a standing wave problem at low frequencies. Based on these analysis results, the DSP adjusts the built-in digital signal processing algorithm to reduce the reverberation effect by increasing the attenuation of specific frequencies, and uses phase cancellation technology to reduce the impact of standing waves. After a series of parameter adjustments, the speaker outputs sound that matches the acoustic characteristics of the room, thereby optimizing the sound quality and providing users with a more immersive listening experience.

[0028] Step S102: According to the acoustic analysis result, automatically adjust the acoustic parameters related to the smart speaker and formulate an acoustic model.

[0029] Using digital signal processing technology, the speaker's equalizer settings, dynamic range and other acoustic parameters are automatically adjusted according to the environmental analysis results.

[0030] After completing the analysis of the acoustic characteristics of the listening environment, the smart speaker of the present invention will use advanced digital signal processing technology to automatically adjust its acoustic parameters to optimize the sound performance. The following are the detailed steps of adaptive adjustment: Based on the acoustic characteristics analysis results, the sound pressure level differences in each frequency band in the room are identified. The gain of each frequency band is adjusted using the following formula, as shown in formula (2).

[0031] Formula (2) in, Indicates the frequency band that needs to be adjusted The sound pressure gain value is Indicates the ideal sound pressure gain value of the target frequency band. Indicates the second sound pressure gain value of the actual measured frequency band.

[0032] This tuning process ensures that the speaker output maintains a flat frequency response across the entire frequency range, thereby overcoming sound quality losses caused by the environment.

[0033] Dynamic range adjustment relies on the evaluation of the ambient noise level. The loudness of the speaker is dynamically adjusted by the following method, as shown in equation (3).

[0034] Formula (3) in, represents the output loudness at time t, Indicates the nominal loudness of the speaker. represents the ambient noise level measured in real time, Indicates the set noise threshold, Represents the adjustment factor.

[0035] This method allows the speaker to automatically increase its output loudness when noise levels are high, ensuring that music details are clearly audible.

[0036] Combined with the algorithm, the sound pressure gain value of the frequency band that needs to be adjusted in unit time t is obtained, as shown in formula (4).

[0037] Formula (4) in, Indicates the frequency band that needs to be adjusted in the end The sound pressure gain value at event t.

[0038] Indicates the original ideal sound pressure gain value of the target frequency band. Represents an adjustment factor that determines the impact of dynamic range adjustment on the frequency band gain. Indicates the output loudness adjusted in real time according to the ambient noise. Indicates the nominal loudness of the sound.

[0039] Taking a real-world scenario as an example, after analyzing the acoustic characteristics of the listening environment, the smart speaker found that the sound pressure level in the 500Hz frequency band was low. According to the above formula, the speaker automatically calculated that a 2dB gain increase was needed to compensate for this frequency band. At the same time, as the ambient noise level increases at night, the speaker dynamically adjusts the output loudness based on real-time noise monitoring results to improve the clarity of the music. Through these adaptive adjustments, users can get a consistent sound quality experience in different listening environments.

[0040] Step S103: Based on the user's listening preferences, an acoustic model matching the user's listening preferences is formulated.

[0041] Using machine learning algorithms, we optimize personalized acoustic models based on user listening habit data and improve the accuracy of acoustic tuning.

[0042] Collect users' listening preference data in different environments and scenarios, including volume settings, frequency band preferences, music type selection, etc.

[0043] The collected data is subjected to feature extraction. Key features may include: user volume adjustment habits, frequency response preferences, the correlation between loudness and environment, and the matching degree between music type and listening environment. The feature extraction process can be expressed using the following formula (5): Formula (5) in, represents the extracted feature vector, Represents the feature extraction function.

[0044] The extracted feature vector is input into the machine learning model for model training. The model design can be a supervised learning framework, as shown in the following formula (6): Formula (6) in, represents the trained personalized acoustic model, represents the learning function, represents a special vector, Indicates the user's listening preference label.

[0045] Based on user feedback and real-time listening data, the personalized acoustic model is continuously optimized and updated to adapt to the user's possibly changing listening habits.

[0046] The second aspect of the present invention provides an intelligent device, including a transmitter, a receiver, a memory and a processor; the memory is used to store computer instructions; the processor is used to run the computer instructions stored in the memory to implement the above-mentioned intelligent speaker adjustment method.

[0047] The third aspect of the present invention provides a storage medium, comprising: a readable storage medium and computer instructions, wherein the computer instructions are stored in the readable storage medium; the computer instructions are used to implement the above-mentioned smart speaker adjustment method.

[0048] The beneficial effects provided by the present invention are as follows: by integrating an advanced intelligent control system, it can automatically identify and adapt to different listening environments, analyze the acoustic characteristics of the environment in real time, and use digital signal processing algorithms and machine learning technology to automatically adjust the frequency response and sound directivity of the speaker, thereby providing users with a personalized acoustic experience. While ensuring accuracy, the overall sound quality effect is also greatly improved.

[0049] At the same time, by increasing the attenuation of specific frequencies and reducing the reverberation effect, the speaker output is matched with the acoustic characteristics of the environment, achieving the optimization of sound quality following the environment, while bringing users a more immersive listening experience.

[0050] Obviously, the above specific implementation cases are only examples for illustrating the application of the present method, rather than limiting the implementation methods. For those skilled in the art, other different forms of changes and modifications can be made on the basis of the above description to study other related issues. Therefore, the protection scope of the present invention should be the protection scope of the claims.

[0051] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0052] The electronic device and other embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0053] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0054] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, rather than to limit them. Although the embodiments of the present invention have been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

[0055] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be regarded as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0056] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for adjusting a smart speaker, characterized in that: The method comprises S101: Collecting sound data of the environment where the smart speaker is located, and performing acoustic characteristic analysis on the environment; S102: Automatically adjust acoustic parameters related to the smart speaker according to the acoustic analysis result and formulate an acoustic model; S103: In combination with the user's listening preference, an acoustic model matching the user's listening preference is formulated.

2. The method according to claim 1, characterized in that The sound data includes: sound timbre data, sound frequency and sound amplitude.

3. The method according to claim 2, characterized in that The acoustic characteristic analysis of the environment includes: the sound timbre data, sound frequency and sound amplitude are analyzed by a digital signal processor to identify acoustic parameters related to the sound data.

4. The method according to claim 2, characterized in that: The performing acoustic characteristic analysis on the environment further includes: detecting whether there are acoustic defects in the environment by adjusting the sound pressure level of the microphone, as shown in formula (1), Formula (1) in, Indicates the severity of the acoustic defect, represents the sound pressure level of the i-th microphone, Represents the average of the sound pressure level measurements from all microphones.

5. The method according to claim 4, characterized in that The step of automatically adjusting acoustic parameters related to the smart speaker according to the acoustic analysis result includes: Adjust the gain value of each frequency band of the environment, as shown in formula (2), Formula (2) in, Indicates the frequency band that needs to be adjusted The sound pressure gain value is Indicates the first sound pressure gain value of the target frequency band, Indicates the second sound pressure gain value of the actual measured frequency band.

6. The method according to claim 5, characterized in that In S103, combining the listening preferences of the user, formulating an acoustic model that matches the listening preferences of the user includes: Collecting users’ listening preference data; The listening preference data is feature extracted as first listening preference data, and the first listening preference data is input into the acoustic model to obtain a listening preference acoustic model matching the user.

7. A smart device, characterized in that: include: transmitter, receiver, memory and processor; The memory is used to store computer instructions; The processor is used to run the computer instructions stored in the memory to implement the adjustment method of the smart speaker according to any one of claims 1 to 6.

8. A storage medium, characterized in that: include: A readable storage medium and computer instructions, wherein the computer instructions are stored in the readable storage medium; The computer instructions are used to implement the adjustment method of the smart speaker according to any one of claims 1 to 6.

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