Smart speaker audio enhancement method based on magnetic position and environmental characteristics

Abstract

The present invention provides an audio enhancement method for a smart speaker based on magnetic adsorption position and environmental characteristics. The method detects the current magnetic adsorption position type and magnetic adsorption angle of the speaker, collects the surrounding environmental characteristic data and environmental noise data, and realizes sound effect optimization. The material characteristics of the reflective surface are determined according to the magnetic adsorption position type, the sound wave reflection path is calculated in combination with the room structure characteristics, the reverberation time and reflection gain of the audio signal are adjusted, and a sound diffusion pattern is generated and used for spatial sound field reconstruction. At the same time, different frequency bands are compensated according to the distribution of sound-absorbing materials, and a frequency response compensation curve is generated to enhance the sound effect of the attenuation frequency band. The sound wave radiation path is calculated according to the magnetic adsorption angle, and the phase difference and gain ratio of the sound unit are adjusted to realize a directional sound field; the high-frequency gain and propagation attenuation are dynamically adjusted in a dimly lit or high-humidity and low-temperature environment. In addition, a cancellation signal opposite to the noise is generated through spectrum analysis and superimposed on the audio signal to achieve an active noise reduction effect.

Description

Technical Field

[0001] The present invention relates to the technical field of speaker audio processing, and in particular to a smart speaker audio enhancement method based on magnetic position and environmental characteristics. Background Art

[0002] In the existing technology, the audio processing methods of smart speakers generally focus on optimizing sound effects through preset sound field modes and simple acoustic algorithms to adapt to different environments and listening needs. Most smart speakers have basic environmental adaptability capabilities, such as automatic volume adjustment, simple echo suppression, and basic noise cancellation. Some advanced smart speakers have also introduced multi-microphone arrays and algorithms to improve the sound transmission effect of the speakers in different spaces. However, most of these optimizations are static and lack adaptive adjustment to dynamic environmental characteristics. In particular, there are still limitations in optimizing sound effects under different reflective materials and complex spatial environments.

[0003] Currently, some smart speakers feature a magnetic ring on the bottom. This design allows them to attach directly to metal surfaces such as refrigerators and cabinets, providing users with flexible installation options. However, to accommodate a variety of non-metal surfaces, the speakers can also be used with magnetic brackets or auxiliary attachment accessories with metal frames, allowing them to attach to glass, walls, or furniture with metal frames. This allows users to flexibly mount the speakers on different surfaces and at different angles to achieve the ideal listening experience. However, due to differences in surface materials and attachment angles, the sound waves emitted by the speakers exhibit different characteristics during propagation and reflection. For example, when a speaker is attached to a refrigerator, glass, wall, or furniture with metal frames, the reflection intensity, directionality, and reverberation effect of the sound waves will vary. Furthermore, the magnetic attachment angle of the speaker affects the propagation path of the sound waves in space, thereby affecting the sound field coverage and sound quality.

[0004] A major problem with existing technologies is that smart speakers struggle to achieve refined sound enhancement under varying magnetic attachment positions and environmental characteristics. When attached to different surfaces or placed in different room locations, the sound wave's reflection characteristics, reverberation time, and sound field distribution are affected, resulting in inconsistent sound performance. Furthermore, environmental characteristics such as furniture density, the distribution of sound-absorbing materials, light intensity, and temperature and humidity all affect sound transmission and auditory comfort. Existing speaker processing methods struggle to effectively address these changing environmental factors and are unable to automatically adjust sound performance to suit specific environments.

[0005] Therefore, it is necessary to develop an audio enhancement method for smart speakers based on magnetic position and environmental characteristics. Summary of the Invention

[0006] This application provides a smart speaker audio enhancement method based on magnetic position and environmental characteristics to improve the user's auditory experience.

[0007] This application provides a smart speaker audio enhancement method based on magnetic position and environmental characteristics, including:

[0008] Detecting the current magnetic adsorption position type and magnetic adsorption angle of the smart speaker, and collecting environmental feature data and ambient noise data around the smart speaker; wherein the magnetic adsorption position types include metal planes, glass surfaces, wall surfaces, and furniture surfaces with metal frames; the environmental feature data includes room size, furniture density, sound-absorbing material distribution, ambient light intensity, and ambient temperature and humidity;

[0009] Determining the material characteristics of the reflective surface according to the magnetic adsorption position type;

[0010] Calculating a sound wave reflection path based on the material properties of the reflective surface, the room size, and the furniture density; adjusting the reverberation time and reflection gain of the audio signal based on the sound wave reflection path to generate a sound diffusion pattern adapted to the current space; and reconstructing the spatial sound field of the input audio signal using the sound diffusion pattern;

[0011] Based on the distribution of the sound absorbing material, different frequency bands of the audio signal are compensated to generate a frequency response compensation curve, wherein the compensation curve is used to enhance the frequency band attenuated by the sound absorbing material;

[0012] Calculating the radiation path of the sound wave in space according to the magnetic adsorption angle; and adjusting the phase difference and gain ratio of each sound unit of the speaker according to the radiation path to achieve a directional sound field;

[0013] When the ambient light intensity is lower than a preset threshold, the gain of the high frequency band of the audio signal is reduced; and the propagation attenuation of the audio signal is compensated according to the temperature and humidity data;

[0014] The ambient noise data is subjected to spectrum analysis to generate a cancellation signal having a spectrum opposite to that of the ambient noise, and the cancellation signal is superimposed on the original audio signal to achieve active noise reduction.

[0015] Furthermore, the smart speaker audio enhancement method based on magnetic position and environmental characteristics further includes:

[0016] Providing a user interaction interface to the user, wherein the user interaction interface allows the user to adjust the reverberation time and reflection gain, the frequency band gain of the frequency response compensation curve, the phase difference and gain ratio of the sound unit, and the amplitude of the cancellation signal;

[0017] Detecting and recording parameter adjustment operations performed by the user through the user interaction interface;

[0018] Using a machine learning algorithm, the parameter adjustment operation is associated with the current magnetic adsorption position type and environmental feature data to establish a user sound effect preference model;

[0019] When a new magnetic adsorption position and environmental features are detected, they are input into the user sound preference model to predict the target audio processing parameters; and the target audio processing parameters are applied to the audio signal processing of the smart speaker.

[0020] Furthermore, the detecting of the current magnetic adsorption position type and magnetic adsorption angle of the smart speaker and the collection of environmental feature data and environmental noise data around the smart speaker include:

[0021] Use multiple sensors to detect the smart speaker's magnetic adsorption location type in real time, determining whether the speaker is currently adsorbed on a metal surface, glass surface, wall surface, or furniture with a metal frame;

[0022] The angle sensor is used to obtain the current magnetic adsorption angle of the smart speaker and record the tilt angle of the speaker relative to the horizontal plane.

[0023] Collect characteristic data of the speaker's surrounding environment, including room size, furniture density, distribution of sound-absorbing materials, ambient light intensity, and temperature and humidity parameters, as well as obtain noise data in the current environment;

[0024] The collected environmental feature data and magnetic adsorption position type information are stored in a storage module of the speaker.

[0025] Furthermore, determining the material characteristics of the reflective surface according to the magnetic adsorption position type includes:

[0026] Metal planes correspond to high reflectivity acoustic properties;

[0027] Glass surfaces correspond to medium reflectivity acoustic properties;

[0028] The wall surface corresponds to low reflectivity acoustic properties;

[0029] Furniture surfaces with metal frames correspond to mixed reflectivity acoustic properties.

[0030] Furthermore, the method further comprises calculating a sound wave reflection path in combination with the material properties of the reflecting surface, the room size, and the furniture density; adjusting the reverberation time and reflection gain of the audio signal according to the sound wave reflection path to generate a sound diffusion pattern adapted to the current space; and reconstructing the spatial sound field of the input audio signal using the sound diffusion pattern, including:

[0031] Analyze the propagation characteristics of sound waves in the room, including reflection, absorption, and scattering paths, based on the material properties of the reflective surface, the size of the room, and the density of furniture;

[0032] Adjust the reverberation time of the audio signal according to the sound wave reflection path to ensure that the sound output by the speaker has adaptive sound performance on different reflection surfaces;

[0033] By adjusting the reflection gain and optimizing the sound diffusion pattern, the sound effect is made more uniform at different locations in the room, and the sound diffusion pattern is used to reconstruct the spatial sound field of the input audio signal to adapt to the spatial characteristics of the current room.

[0034] The beneficial effects of the technical solution provided by this application include:

[0035] (1) This method can adjust the sound output in real time according to the magnetic adsorption position type and angle of the smart speaker, automatically identify the reflection characteristics of different material surfaces such as metal, glass, and wall, thereby adjusting the reverberation time and reflection gain of the audio signal and generating a sound diffusion pattern suitable for the current environment. This adaptive optimization significantly improves the sound performance of the speaker in different positions and environments, allowing users to always have the best listening experience. (2) By analyzing the distribution of sound-absorbing materials in the room, this method can compensate for different frequency bands of the audio signal, generate a frequency response compensation curve, and enhance the sound effect of the frequency band attenuated by the sound-absorbing material. This frequency band compensation function improves the clarity and fullness of the sound, allowing high-quality audio performance to be obtained even in an environment with sound-absorbing materials. (3) The sound wave radiation path is calculated based on the magnetic adsorption angle of the speaker, and the phase difference and gain ratio of each sound unit are adjusted to achieve sound field optimization in a specific direction. This function enables the speaker to achieve a directional sound field at different installation angles and positions, improving the coverage and sense of direction of the sound, and bringing a more immersive listening experience to the user. (4) By analyzing the spectrum of the ambient noise data, a cancellation signal is generated and superimposed on the original audio signal, actively reducing the interference of external noise on the sound effect. This active noise reduction function can effectively improve the clarity of audio in noisy environments, allowing the speaker to provide high-quality sound output in various environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flowchart of a smart speaker audio enhancement method based on magnetic position and environmental characteristics provided in the first embodiment of the present application. DETAILED DESCRIPTION

[0037] The following description sets forth many specific details to facilitate a thorough understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the scope of the present application. Therefore, the present application is not limited to the specific implementations disclosed below.

[0038] The first embodiment of the present application provides a method for enhancing the audio quality of a smart speaker based on magnetic position and environmental characteristics. Figure 1 , which is a schematic diagram of the first embodiment of the present application. Figure 1 The first embodiment of the present application provides a detailed description of a smart speaker audio enhancement method based on magnetic position and environmental characteristics.

[0039] Step S101: Detect the current magnetic adsorption position type and magnetic adsorption angle of the smart speaker, and collect environmental feature data and environmental noise data around the smart speaker; wherein the magnetic adsorption position type includes metal planes, glass surfaces, wall surfaces, and furniture surfaces with metal frames; the environmental feature data includes room size, furniture density, sound-absorbing material distribution, ambient light intensity, and ambient temperature and humidity.

[0040] Step S101 involves detailed detection and collection of the magnetic adsorption position, magnetic adsorption angle, surrounding environment characteristic data and ambient noise data of the smart speaker. The magnetic adsorption position detection of the smart speaker is intended to identify the type of surface to which the speaker is currently adsorbed. These surface types may include metal planes, glass surfaces, wall surfaces or furniture surfaces with metal frames. The speaker can determine the specific type of adsorption through a built-in sensor system, such as a magnetic field sensing sensor or a contact detection module. This detection mechanism relies on the differences in the responses of different surfaces to magnetism or conductivity. The speaker system can automatically determine the current adsorption surface type based on these differences. For example, a metal surface will show a higher magnetic field induction value, while a glass or wall surface will show a relatively low value.

[0041] While the magnetic adsorption position is determined, the magnetic adsorption angle of the speaker also needs to be measured in real time. Angle measurement can be achieved through a built-in angle sensor (such as a gyroscope or accelerometer) to obtain the precise tilt and rotation direction of the speaker relative to the horizontal or vertical plane. For example, when the speaker is adsorbed on the wall, the angle sensor can detect the rotation angle of the speaker to determine the direction of the speaker in space. This angle information is important for subsequent sound optimization, because different angles affect the emission direction and reflection path of the sound wave.

[0042] After obtaining the magnetic adsorption position type and adsorption angle, the smart speaker continues to collect environmental feature data. First, the speaker uses a laser rangefinder or ultrasonic rangefinder to measure the size of the room to obtain the basic structural parameters of the indoor space, including the length, width, and height of the room. Secondly, the speaker's sensor system can detect the density of furniture. This step may be achieved through a distance sensor or image sensor (such as a camera) combined with an image recognition algorithm to identify the distribution of furniture in the room and its density. The density of furniture will significantly affect the reflection and absorption characteristics of sound, so this data is crucial for adjusting sound effects.

[0043] At the same time, the speaker also collects information about the distribution of sound-absorbing materials, such as the specific locations of carpets, curtains, cushions, and other sound-absorbing materials. This information can be obtained through an image recognition system or a pre-set database. The speaker can compare the detected image data with the characteristics of the sound-absorbing materials and automatically determine the location and coverage area of ​​the sound-absorbing materials in the room. In addition, the ambient light intensity is measured by a built-in light sensor, which can record changes in light brightness to determine the lighting conditions of the environment. The speaker will adjust the gain of certain high-frequency sound effects based on the light intensity measurement results to ensure that users have a comfortable listening experience in low-light conditions.

[0044] The speaker also uses a temperature and humidity sensor to measure the ambient temperature and humidity in real time. Temperature and humidity directly affect air density and sound propagation characteristics, making this information crucial for subsequent audio attenuation compensation. After collecting this data, the smart speaker uses its built-in microphone array to acquire ambient noise data. The microphones perform spectral analysis on the captured ambient sound signals to identify the frequency and intensity distribution of background noise, providing a reference for subsequent active noise reduction operations.

[0045] To sum up, step S101 enables the smart speaker to adapt to the environment by collecting multiple data on the magnetic adsorption position type, adsorption angle, environmental characteristics and noise, providing comprehensive basic data support for subsequent sound effect optimization and directional sound field control.

[0046] Furthermore, the detecting of the current magnetic adsorption position type and magnetic adsorption angle of the smart speaker and the collection of environmental feature data and environmental noise data around the smart speaker include:

[0047] Use multiple sensors to detect the smart speaker's magnetic adsorption location type in real time, determining whether the speaker is currently adsorbed on a metal surface, glass surface, wall surface, or furniture with a metal frame;

[0048] The angle sensor is used to obtain the current magnetic adsorption angle of the smart speaker and record the tilt angle of the speaker relative to the horizontal plane.

[0049] Collect characteristic data of the speaker's surrounding environment, including room size, furniture density, distribution of sound-absorbing materials, ambient light intensity, and temperature and humidity parameters, as well as obtain noise data in the current environment;

[0050] The collected environmental feature data and magnetic adsorption position type information are stored in a storage module of the speaker.

[0051] In this embodiment, the smart speaker first uses multiple sensors to detect its current magnetic adsorption position type. These sensors include magnetic field sensors and material identification sensors, which can identify the surface material characteristics of the speaker adsorbed. The smart speaker will exhibit different magnetic field signal characteristics in response to different surface materials. For example, the magnetic field sensor will sense a strong magnetic signal on a metal surface, while it will be relatively weak on a glass surface or wooden furniture surface. Based on these magnetic field and material characteristics, the system can accurately determine whether the speaker is currently adsorbed on a metal plane, glass surface, wall surface, or furniture surface with a metal frame. This position type information is extremely important for sound optimization, because different surface materials will have different effects on sound wave reflection, absorption, and diffusion.

[0052] After determining the speaker's magnetic attachment position type, the smart speaker uses an angle sensor to obtain its current magnetic attachment angle. Angle sensors, such as accelerometers, gyroscopes, or electronic compasses, measure the speaker's tilt angle and direction relative to the horizontal plane. This angle data helps the system calculate the direction of sound wave propagation in space, as the speaker's sound emission direction changes depending on the tilt angle. This angle data provides critical information for subsequent audio signal processing, helping the system determine the sound wave's transmission path and reflection angle.

[0053] After collecting position and angle information, the smart speaker also collects data on the surrounding environmental characteristics. Using a built-in laser rangefinder or ultrasonic sensor, the system can measure the room's size to obtain its length, width, and height. Room size significantly affects sound propagation. Small spaces may produce more reflections and reverberation, while large spaces may cause sound to diffuse too quickly, affecting the listening experience. Furthermore, the smart speaker uses distance sensors or image recognition technology to assess the density of furniture in the room. This allows it to identify the number, location, and volume distribution of furniture in the room. The distribution of furniture affects the reflection and absorption characteristics of sound. High-density furniture may increase sound wave attenuation, reducing the speaker's sound quality.

[0054] In addition, the speaker uses infrared or image sensors to detect the distribution of sound-absorbing materials in the room, such as the location of sound-absorbing materials such as curtains, carpets or sofas. Sound-absorbing materials have strong absorption of the high-frequency bands of sound propagation. Identifying the distribution of these materials can help the system make targeted adjustments in sound processing. Through the ambient light sensor, the speaker can also detect the current light intensity to reduce the volume of high-frequency bands in darker environments to avoid harsh sound effects for users. In terms of temperature and humidity detection, the speaker is equipped with temperature and humidity sensors to obtain the temperature and humidity parameters of the air. Changes in temperature and humidity will affect the speed and attenuation of sound propagation, so these data provide a reference for sound effect compensation.

[0055] After collecting the magnetic position, angle, and environmental characteristics, the smart speaker stores all collected data in its internal storage module. This data provides the basis for subsequent processing and optimization of the speaker, enabling it to optimize audio output in real time based on the specific conditions of the current environment to ensure the best listening experience.

[0056] Step S102: determining the material characteristics of the reflective surface according to the magnetic adsorption position type.

[0057] The core of step S102 is to determine the reflective surface material characteristics of the adsorption surface according to the current magnetic adsorption position type of the smart speaker, so as to optimize the sound output in subsequent steps. The smart speaker first identifies the surface type of the magnetic adsorption position through the data collected in step S101. These surface types may include metal planes, glass surfaces, wall surfaces, and furniture surfaces with metal frames. The acoustic properties of each surface material are different, and therefore have different requirements for sound optimization. To this end, it is necessary to quantify the reflection characteristics of different surfaces so that the smart speaker can adjust the audio signal processing parameters according to the sound wave reflection characteristics of the surface material.

[0058] After identifying the current magnetic adsorption surface type, the system will search the corresponding preset reflection characteristic database, which stores acoustic parameters such as reflection coefficient, absorption coefficient and scattering coefficient of common materials. For example, for metal planes, the database will store its reflection characteristic parameters under high-frequency and low-frequency sound waves. Generally speaking, the reflectivity of metal surfaces for high-frequency sounds is higher, while for low-frequency sounds, it may exhibit stronger absorption or scattering characteristics. Similarly, glass surfaces usually have higher mid- and high-frequency reflection characteristics, but weaker reflectivity for low frequencies. Wall surfaces tend to have medium reflectivity, especially in the case of concrete or masonry materials, which can exhibit strong reflection effects in the mid- and low-frequency bands. For furniture surfaces with metal frames, the reflection characteristics may be affected by the combination of metal parts and other materials (such as wood or fabric). The reflection effect of such surfaces is generally more complex, usually manifested as different degrees of reflection or absorption of sounds in different frequency bands.

[0059] By matching the magnetic attachment location type with the acoustic parameters in the database, the smart speaker obtains the specific reflective characteristics of the surface material, including the reflection coefficient and absorption coefficient. The speaker then further considers how the surface's reflectivity varies with frequency—that is, how effectively the surface reflects and absorbs sound waves at different frequencies. Based on this frequency-dependent characteristic, the speaker calculates the surface's reflection gain and absorption loss for specific frequency bands.

[0060] Additionally, speakers take the roughness or smoothness of the surface material into account. Generally speaking, smooth metal or glass surfaces reflect sound waves more concentratedly, while rough walls or furniture surfaces can lead to stronger scattering effects. This surface roughness directly affects the reflection path and diffusion of sound waves, which in turn affects reverberation time and the distribution of the spatial sound field. Therefore, after obtaining the basic characteristics of the reflective surface material, the system will comprehensively consider the influence of surface smoothness or roughness through a built-in calculation model to more accurately model the reflection behavior of different materials.

[0061] After completing the analysis of the material properties of the reflective surface, the smart speaker system will store these parameters in a temporary data cache for use in subsequent steps. By clearly identifying and quantifying the reflective characteristics of the magnetic adsorption surface type, the speaker can use this data to adjust the sound output in real time during the subsequent sound processing steps, thereby providing a more optimized audio experience at different magnetic adsorption positions. This processing method ensures that the speaker's sound performance on surfaces of different materials is optimal, and can be adaptively adjusted according to the acoustic characteristics of different surfaces, making the speaker more adaptable and providing a better user experience in complex home environments.

[0062] Furthermore, determining the material characteristics of the reflective surface according to the magnetic adsorption position type includes:

[0063] Metal planes correspond to high reflectivity acoustic properties;

[0064] Glass surfaces correspond to medium reflectivity acoustic properties;

[0065] The wall surface corresponds to low reflectivity acoustic properties;

[0066] Furniture surfaces with metal frames correspond to mixed reflectivity acoustic properties.

[0067] In this embodiment, the smart speaker determines the acoustic properties of the reflective surface material based on the type of magnetic adsorption location detected, thereby optimizing the sound wave reflection characteristics of different surfaces. When the speaker detects that its magnetic adsorption location is a metal surface, the system automatically recognizes the high reflectivity of the metal. Metal surfaces reflect sound waves very strongly, especially high-frequency sound waves, resulting in high sound reflection gain and low sound absorption. Therefore, in this case, the smart speaker will make corresponding sound adjustments based on the high reflectivity characteristics to avoid overly sharp high-frequency reflections in the sound effects, making the listening experience more comfortable.

[0068] When the smart speaker detects a glass surface as the magnetic attachment location, the system recognizes that glass has medium reflectivity. Glass significantly reflects mid- and high-frequency sound waves, but this effect is weaker than that of metal. Therefore, the smart speaker adjusts the audio signal appropriately based on glass's medium reflectivity to ensure clear sound without excessive reflection when attached to the glass surface, especially to prevent unnecessary echo interference in smaller spaces.

[0069] When the speaker is attached to a wall, the system detects that the wall has low sound wave reflectivity. Walls are typically made of concrete, brick, or plaster, which have low sound reflectivity, particularly absorbing high frequencies in the mid- and low-frequency ranges. Upon detecting the wall's material, the smart speaker increases the sound reflection gain based on this low-reflectivity, compensating for some of the sound wave attenuation and resulting in a fuller and more balanced sound. This low reflectivity requires the speaker to enhance the sound performance by appropriately increasing reverberation to provide a more ideal listening experience in low-reflectivity environments.

[0070] When the smart speaker is attached to the surface of furniture with a metal frame, the system recognizes that the surface has acoustic properties with mixed reflectivity. Furniture surfaces with metal frames may contain metal, wood, or other soft materials, and the combination of these materials makes the reflection characteristics of sound waves more complex. The smart speaker will make multi-level adjustments based on this mixed characteristic. For example, in the high-frequency band, it reduces the gain based on the reflective properties of metal, while in the mid- and low-frequency bands, it increases the compensation based on the sound absorption properties of soft materials. This allows the speaker to adapt to the mixed reflective environment and provide a balanced sound performance, ensuring that the sound effects remain clear and well-defined when attached to the furniture surface.

[0071] Through the smart speaker's recognition and corresponding adjustment of the acoustic characteristics of different adsorption surfaces, the system can automatically adjust the audio output according to the characteristics of surface materials such as metal, glass, walls, and furniture with metal frames, so that the sound effects are more in line with the acoustic requirements of the current adsorption environment, thereby providing users with a more optimized listening experience.

[0072] Step S103: Calculate the sound wave reflection path based on the material properties of the reflecting surface, the room size, and the furniture density; adjust the reverberation time and reflection gain of the audio signal according to the sound wave reflection path to generate a sound diffusion pattern adapted to the current space; and use the sound diffusion pattern to reconstruct the spatial sound field of the input audio signal.

[0073] In step S103, the smart speaker first calculates the reflection path of the sound wave in the room based on the material properties of the reflective surface, the room size, and the furniture density information determined in step S102. This calculation process is achieved by constructing a three-dimensional spatial sound field model. Specifically, the smart speaker uses the acquired room size data (including the length, width, and height of the room) to construct a virtual three-dimensional room model. This model is further divided into multiple acoustic units, representing possible reflection points of the sound waves. The speaker maps the material properties of each reflective surface to these units. For example, metal surfaces, high-density furniture surfaces, etc. each have different sound wave reflection and absorption characteristics.

[0074] In the three-dimensional model, the speaker sets the reflection coefficient and absorption coefficient for different reflective surfaces based on the aforementioned reflective surface material properties. Then, the smart speaker system applies a ray tracing algorithm to simulate the path of the sound wave when it starts from the sound-emitting unit and encounters different reflective surfaces. The ray tracing algorithm allows the system to track multiple reflections of the sound wave and accurately calculate the propagation distance, reflection angle, and energy attenuation of the sound wave after each collision. Specifically, when simulating the sound wave path, the speaker determines the attenuation of the sound wave energy based on the characteristics of the reflective material. For example, sound waves will be effectively reflected on metal surfaces with high reflectivity, while on soft material surfaces with sound-absorbing properties, the sound wave energy will be significantly reduced. During this process, the speaker will record the total length of each reflection path and the angle of each reflection to obtain complete sound wave propagation path information.

[0075] Based on this reflection path data, the smart speaker further adjusts the reverberation time of the audio signal. Reverberation time is adjusted based on the path length, room volume, and the room's reflective properties. For sounds with longer reflection paths, the system may increase the reverberation time to make the sound fuller when it reaches the listener's ears. For sounds with shorter reflection paths, the system may reduce the reverberation time to avoid the muddiness caused by excessive reflections. This adjustment is achieved by controlling the reverberation effect and reflection gain in the sound signal processing. Adjusting the reflection gain ensures that the energy of the sound on each reflection path is more evenly distributed when it propagates to different areas of the room. The smart speaker dynamically adjusts the gain based on the path length and the reflection coefficient of the material. For example, in cases where the reflection path is long and the energy attenuation is significant, the speaker can compensate for the energy loss by increasing the reflection gain, while in cases where the reflection path is short, the gain is reduced accordingly to avoid the sound being too sharp or unnatural.

[0076] The adjusted sound wave propagation and reflection data are compiled into a "sound diffusion pattern", which is an overall description of the sound propagation characteristics in the room. The sound diffusion pattern is not a filter directly applied to signal processing, but rather a spatial sound field characteristic model that describes different reflection paths, the distribution of reflective surfaces, and energy attenuation. This pattern provides the smart speaker with a complete spatial sound field map, enabling the speaker to optimize the sound output more specifically during signal processing. Next, the smart speaker uses the sound diffusion pattern to reconstruct the spatial sound field, a process that relies on digital signal processing algorithms (DSP). Using the reflection path and gain information provided by the sound diffusion pattern, the smart speaker processes the input audio signal so that the output sound propagates and diffuses naturally in the room.

[0077] During the spatial sound field reconstruction process, the smart speaker fine-tunes the sound in different frequency bands based on the path data recorded in the sound diffusion pattern, ensuring consistent clarity and three-dimensionality in all directions within the room. The smart speaker also adjusts the sound signal to the optimal state through phase and gain control, ensuring a balanced and natural sound experience for listeners everywhere in the room.

[0078] Furthermore, the method further comprises calculating a sound wave reflection path in combination with the material properties of the reflecting surface, the room size, and the furniture density; adjusting the reverberation time and reflection gain of the audio signal according to the sound wave reflection path to generate a sound diffusion pattern adapted to the current space; and reconstructing the spatial sound field of the input audio signal using the sound diffusion pattern, including:

[0079] Analyze the propagation characteristics of sound waves in the room, including reflection, absorption, and scattering paths, based on the material properties of the reflective surface, the size of the room, and the density of furniture;

[0080] Adjust the reverberation time of the audio signal according to the sound wave reflection path to ensure that the sound output by the speaker has adaptive sound performance on different reflection surfaces;

[0081] By adjusting the reflection gain and optimizing the sound diffusion pattern, the sound effect is made more uniform at different locations in the room, and the sound diffusion pattern is used to reconstruct the spatial sound field of the input audio signal to adapt to the spatial characteristics of the current room.

[0082] In this embodiment, the smart speaker combines the characteristics of the reflective surface material, the size of the room, and the density of furniture to accurately calculate the reflection path of the sound waves in the room to optimize the spatial performance of the sound effect. First, the system will perform a detailed analysis of the propagation characteristics of the sound waves in the current room, including the reflection, absorption, and scattering paths of the sound waves. The material characteristics of the reflective surface, such as metal or glass surfaces, will affect the reflection intensity and direction of the sound waves; the size of the room affects the total propagation distance of the sound waves, and the density of furniture changes the complexity of the reflection path and the absorption of the sound waves. By analyzing these factors, the speaker system can predict the performance of the sound waves on each reflection path, thereby clarifying which positions will produce strong reflections and which positions will absorb more.

[0083] After obtaining these sound wave reflection paths, the smart speaker adjusts the audio signal's reverberation time accordingly. Reverberation time is a key factor influencing the spatial and natural quality of sound. In large spaces or highly reflective environments, the system appropriately extends the reverberation time to enhance the sound's richness and create a sense of spatial immersion. In small rooms or environments with dense furniture, the reverberation time is appropriately shortened to prevent excessive echoes from blurring the sound. Therefore, the speaker dynamically adjusts the reverberation time based on the current room's sound wave reflection paths, ensuring consistent listening experience across different room types and sizes.

[0084] Next, the smart speaker optimizes the sound diffusion pattern by adjusting the reflection gain. This adjustment allows the speaker to evenly distribute sound energy across different areas of the room. For example, in certain areas of the room, the sound may be muffled due to high sound absorption by reflective surfaces. In these areas, the system increases the reflection gain to ensure clarity. In other areas where reflections may be excessive, the system reduces the reflection gain to avoid sound that is too sharp or harsh. By precisely adjusting the gain of each reflection path, the speaker can achieve uniform sound performance throughout the room.

[0085] Finally, based on the adjusted reverberation time and reflection gain, the smart speaker generates a sound diffusion pattern tailored to the spatial characteristics of the current room. This pattern describes the optimal propagation path and energy distribution of sound waves within the room, used to reconstruct the spatial sound field. The smart speaker uses this sound diffusion pattern to process the input audio signal in real time, using digital signal processing algorithms to ensure that the audio output is more consistent with the acoustic characteristics of the current room. This spatial sound field reconstruction makes the sound diffusion within the room more natural and three-dimensional, ensuring a consistent and clear sound experience regardless of the user's location in the room.

[0086] Step S104: Based on the distribution of the sound absorbing material, different frequency bands of the audio signal are compensated to generate a frequency response compensation curve, where the compensation curve is used to enhance the frequency band attenuated by the sound absorbing material.

[0087] In step S104, the smart speaker compensates for different frequency bands of the audio signal based on the detected distribution of sound-absorbing materials to generate a frequency response compensation curve. This process aims to compensate for the frequency bands absorbed and attenuated by sound-absorbing materials (such as carpets, curtains, or cushions) in the room based on their distribution and characteristics, thereby ensuring that the output sound remains clear and balanced within the room.

[0088] The smart speaker first builds a sound absorption model based on the distribution of sound-absorbing materials. This model includes the specific location of each sound-absorbing material area, the material type, and its sound absorption characteristics at different frequency bands. To achieve this, the smart speaker may use an image recognition system, preset environmental information, or manual user input to determine the location and type of each sound-absorbing material in the room. Each sound-absorbing material has different absorption characteristics at different frequencies. For example, carpets and fabrics generally have a stronger absorption effect in the mid- and low-frequency bands, while thinner curtains may have a more significant sound absorption effect in the high-frequency bands.

[0089] After determining the location and sound absorption characteristics of the sound-absorbing material, the smart speaker will analyze the energy loss of sound waves in different frequency bands when passing through these sound-absorbing areas. For example, for carpet-covered areas distributed at the edges of the room, mid- and low-frequency sound waves will experience significant energy attenuation during propagation due to the sound absorption characteristics of the carpet. The smart speaker will generate gain compensation parameters for each frequency band based on this attenuation information. Specifically, the system will analyze each frequency band separately, calculate the attenuation of the sound wave when propagating through the sound-absorbing area, and generate a corresponding gain compensation value for adjustment during audio output. This gain compensation process ensures that the portion of the sound attenuated by the sound-absorbing material in each frequency band can be compensated, so that the output sound effect is balanced across the entire frequency range.

[0090] To achieve this compensation, the smart speaker generates a frequency response compensation curve based on the frequency-dependent characteristics of the sound absorption model. This compensation curve reflects the gain adjustment values ​​for different frequency bands. For example, a larger gain compensation may be required in the mid- and low-frequency bands, while a smaller compensation value may be required in the high-frequency bands. This compensation curve is then applied to the audio signal processing. When the speaker system outputs the audio signal, it adjusts the gain of each frequency band in real time based on the compensation curve to ensure the sound is balanced across the entire frequency range.

[0091] Generating a frequency response compensation curve requires comprehensive consideration of the distribution of sound-absorbing materials within the room, their absorption coefficients, and the materials' frequency-dependent characteristics. The smart speaker processes the audio signal's various frequency bands through its digital signal processing (DSP) module and adjusts gain band by band based on the gain parameters provided by the compensation curve. This approach effectively compensates for the attenuation of each frequency band by the sound-absorbing materials, maintaining sound clarity and layering regardless of listener position, resulting in a more realistic and balanced sound quality.

[0092] In practice, the DSP module adjusts the gain of each frequency band based on the frequency response compensation curve, applying attenuation compensation to the real-time audio signal. For example, if the low-frequency band has high absorption, the system will increase the gain in that band; while the high-frequency band, with less absorption, will receive a relatively lower gain increase. This compensation process not only enhances the fullness of the sound but also significantly improves the detail and realism of the listening experience in highly absorbent rooms, thereby providing consistent high-quality sound under various absorption conditions.

[0093] Furthermore, based on the distribution of the sound absorbing material, different frequency bands of the audio signal are compensated to generate a frequency response compensation curve, wherein the compensation curve is used to enhance the frequency band attenuated by the sound absorbing material, including:

[0094] First, the system needs to obtain the coordinates (x i ,y i , z i ) and sound absorption coefficient α i (f). Here, (x i ,y i , z i ) represents the position coordinates of the i-th sound-absorbing material area in the room, which helps the system understand the position distribution of the sound-absorbing area. i (f) represents the absorption coefficient of the i-th sound absorption area at the target frequency f. i (f) reflects the material's ability to absorb sound waves at a specific frequency, usually obtained through field testing or material property data. For example, carpets and curtains have higher sound absorption coefficients in the mid- and high-frequency bands, while wooden furniture may absorb more in the mid- and low-frequency bands.

[0095] Next, the weighted average absorption coefficient is calculated according to the following formula 5:

[0096]

[0097] Among them, α weighted (f, θ) is the weighted average sound absorption coefficient, which represents the overall sound absorption of the room. This weighted sound absorption coefficient reflects the comprehensive absorption effect of different sound-absorbing materials and is used to guide subsequent frequency compensation.

[0098] N is the total number of sound absorbing material areas, that is, the number of all sound absorbing material areas in the room.

[0099] S i is the surface area of ​​the i-th sound-absorbing material region, which is used to measure the impact of the sound-absorbing material region and is usually measured based on the actual area of ​​the sound-absorbing material.

[0100] S total is the total surface area in the room, i.e. the sum of all reflective and absorptive surface areas, and is used to normalize the weighted effect of all absorbing materials.

[0101] θ is the magnetic adsorption angle of the smart speaker, that is, the tilt angle of the speaker relative to the horizontal plane of the room, which affects the propagation path of sound waves in the room.

[0102] β is the distance attenuation coefficient of the absorption coefficient, which describes how the absorption of sound waves by an absorbing material changes with distance. Generally speaking, the absorption effect gradually decreases as the distance of the sound wave increases from the absorbing material, so the attenuation coefficient β is used to weight the distance.

[0103] d i (λ) is the distance between the magnetic adsorption position of the smart speaker and the i-th sound-absorbing material area, and is calculated using the following formula 6:

[0104]

[0105] Among them, (x, y, z) is the magnetic adsorption position coordinate of the smart speaker, reflecting the specific position of the speaker in the room.

[0106] (x i ,y i , z i ) are the coordinates of the i-th absorber region, helping the system calculate the spatial distance between the speaker and that region. Closer absorbers have a stronger impact on sound waves, so closer absorbers are given a higher weight when calculating the weighted average absorption coefficient.

[0107] The frequency response compensation coefficient is calculated according to the following formula 7:

[0108]

[0109] Where C(f, θ) is the frequency response compensation coefficient, which describes the required compensation strength at the target frequency f and magnetic adsorption angle θ. It is used to guide how the speaker adjusts the gain at that frequency.

[0110] k is the compensation intensity adjustment coefficient, which controls the compensation amplitude. The value of k is usually determined experimentally to achieve the optimal auditory effect.

[0111] θ0 is the reference angle, which is the main direction angle of the speaker's sound and is determined through experiments.

[0112] The enhanced gain G(f) is generated according to the following formula 8:

[0113] G(f)=G base (f)·C(f,θ)(8)

[0114] Among them, G base (f) is the initial gain at the target frequency f, which is determined by the reference value set by the system or the default setting of the speaker.

[0115] The resulting G(f) is used to adjust the different frequency bands of the audio signal, ensuring that the propagation characteristics of the sound within the room meet the user's listening needs. This enhanced gain compensates for the attenuation of sound frequency components by the room's sound-absorbing materials, ensuring a balanced listening experience regardless of the distribution of the room's sound-absorbing materials.

[0116] Step S105: Calculate the radiation path of the sound wave in space according to the magnetic adsorption angle; and adjust the phase difference and gain ratio of each sound unit of the speaker according to the radiation path to achieve a directional sound field.

[0117] In step S105, the smart speaker calculates the radiation path of the sound wave in space based on its current magnetic adsorption angle, and uses this radiation path information to optimize the phase difference and gain ratio of each sound-emitting unit of the speaker, thereby achieving a directional sound field effect. First, the smart speaker obtains its magnetic adsorption angle through the built-in angle sensor. This angle data reflects the tilt and direction of the speaker relative to the adsorption surface. The magnetic adsorption angle not only determines the initial radiation direction of the sound wave, but also affects the propagation and coverage of the sound wave. Therefore, based on this angle, combined with the geometric layout and environmental characteristics of the room, the smart speaker calculates the ideal radiation path of the sound wave in space.

[0118] After determining the initial radiation angle of the sound wave, the system uses a ray tracing algorithm to predict the actual propagation path of the sound wave. The ray tracing algorithm allows the smart speaker to simulate the multiple reflections of the sound wave after it departs from the sound unit, recording the angle and path length of each reflection, and tracking the energy distribution of the sound wave in different directions. Through this method, the speaker can clearly understand how the sound wave is reflected, scattered, and absorbed in the room at the current angle. This process helps the smart speaker accurately understand the distribution of sound waves on different reflective surfaces and spatial areas, so that corresponding adjustments can be made in the control of the sound unit.

[0119] After calculating the ideal radiation path of the sound waves, the smart speaker uses this path information as the basis for adjusting the phase difference of the sound units. Phase difference adjustment is a sound field control technology that applies appropriate phase offsets between different sound units so that sound waves in a specific frequency band are coherently superimposed in the target direction, enhancing the sound intensity in that direction, while interfering in other directions to suppress the sound intensity. For example, when the sound waves need to be concentrated in a specific area, the system will adjust the phase of each sound unit so that it reaches a synchronized state in that direction, thereby achieving enhanced sound wave energy focusing. The accuracy of this phase adjustment depends on the system's calculation of the radiation path to ensure consistent sound field effects at different magnetic adsorption angles.

[0120] In addition to adjusting the phase difference, smart speakers also adjust the gain ratio of each sound unit based on the radiation path information. The purpose of adjusting the gain ratio is to increase the sound intensity in a specific direction while attenuating sound waves in non-target directions. By adjusting the gain ratio, the system accurately distributes the output energy of each sound unit, thereby increasing the sound pressure level in the target area while maintaining a moderate sound pressure level in other directions to prevent excessive sound diffusion. This method enables smart speakers to achieve a more accurate directional sound field effect in actual applications.

[0121] By adjusting the phase difference and gain ratio, the smart speaker provides users with a sound focusing effect at different angles and directions based on the calculated magnetic adsorption angle and radiation path. This directional sound field technology not only improves sound coverage efficiency but also enhances sound clarity, allowing users to obtain the best listening experience in a specific area. Furthermore, due to the method's automatic adaptability, the smart speaker can still achieve the most optimal sound field optimization effect for the current environment through real-time calculation and adjustment after changing the magnetic adsorption position or angle.

[0122] Furthermore, the method calculates the radiation path of the sound wave in space according to the magnetic adsorption angle; and adjusts the phase difference and gain ratio of each sound unit of the speaker according to the radiation path to achieve a directional sound field, including:

[0123] According to the following formula 1, the weighted path length L required for the composite propagation path of the sound waves emitted by the smart speaker to the target listening area in the room is calculated: w :

[0124]

[0125] Among them, L i is the distance the sound wave travels in the i-th reflection path; this distance is determined by the sound wave propagation model and estimated by combining the room structure and the reflection characteristics of the sound wave. When the sound wave emitted from the smart speaker encounters different reflection surfaces, it will produce different path lengths L.i .

[0126] μ is the air attenuation coefficient, which represents the energy loss caused by air resistance when a sound wave propagates through air. The value of the air attenuation coefficient μ is generally known and is affected by factors such as ambient temperature and humidity. It can usually be obtained through preset or measured values.

[0127] α i is the angle between the sound wave in the i-th path and the reflecting surface; this angle refers to the incident angle of the sound wave when it hits the reflecting surface and is closely related to the direction of the reflecting surface. i Calculated based on the positional relationship between the speaker and the reflective surface. The smaller the incident angle, the shorter the effective propagation path of the sound wave, resulting in more significant attenuation in the weighted path.

[0128] N is the maximum number of reflections; α0 is the initial radiation angle, which is calculated using the following formula 2:

[0129]

[0130] Where θ is the magnetic adsorption angle of the smart speaker, that is, the inclination angle of the speaker relative to the horizontal plane; h is the height of the magnetic adsorption position, which refers to the vertical height of the speaker relative to the reference plane of the room (such as the ground); d is the horizontal distance between the speaker and the main reflective surface;

[0131] The phase difference Δφ of the sound unit is determined according to the following formula 3:

[0132]

[0133] Where λ is the wavelength of the sound wave; θ is the magnetic adsorption angle of the smart speaker; L w is the weighted path length required for the complex propagation path of the sound wave in the room, which is calculated using Formula 1.

[0134] The gain ratio G of the sound unit is determined according to the following formula 4:

[0135]

[0136] Among them, A is the sound intensity coefficient, which represents the basic output power of the sound unit, and the overall sound intensity is controlled by this coefficient. w is the weighted path length required for the complex propagation path of the sound wave in the room; μ is the air attenuation coefficient.

[0137] Through these steps, the smart speaker dynamically adjusts the phase difference and gain ratio of each driver based on the current magnetic attachment angle and room environment, ensuring that the sound wave propagation path in the space best meets the needs of the target listening area. Ultimately, this dynamic adjustment enables the speaker to produce an optimal directional sound field at different attachment positions and angles, achieving personalized and high-quality sound output.

[0138] Step S106: When the ambient light intensity is lower than a preset threshold, the gain of the high frequency band of the audio signal is reduced; and the propagation attenuation of the audio signal is compensated according to the temperature and humidity data.

[0139] In step S106, the smart speaker uses its built-in light sensor to monitor ambient light intensity in real time. When it detects that the ambient light intensity falls below a set threshold, it automatically adjusts the gain of the audio signal's high-frequency band, reducing the volume of the high-frequency components. The light sensor continuously monitors changes in indoor light levels and compares the measured value with a preset light intensity threshold. If the current light level falls below this threshold, the smart speaker identifies the environment as dim and appropriately reduces the gain of the high-frequency band to minimize irritation to the user in a dark environment, creating a softer listening experience.

[0140] At the same time, the smart speaker will obtain data from the temperature and humidity sensor to detect the ambient temperature and humidity in real time. Temperature and humidity parameters directly affect the air density, which in turn affects the propagation and attenuation characteristics of sound in the air. In high humidity or low temperature environments, the propagation speed and attenuation rate of sound will change. Especially at lower temperatures, the attenuation of high-frequency sound propagation is more significant. After obtaining these environmental parameters, the system will calculate the attenuation degree of the audio signal in different frequency bands in the current environment based on the impact of temperature and humidity on sound wave propagation, to ensure that the sound effects output by the speaker can maintain consistent sound quality in this environment.

[0141] After calculating the propagation attenuation of the audio signal, the smart speaker adjusts the gain of each frequency band to compensate in real time. Specifically, for high-frequency components that attenuate more rapidly in low-temperature or high-humidity environments, the system appropriately increases their gain to ensure energy balance during sound propagation, resulting in a clear and full sound. In relatively dry or high-temperature environments, where high-frequency attenuation is less severe, the system can reduce the compensation for high-frequency gain to maintain a natural sound.

[0142] This gain adjustment process is performed by the speaker's digital signal processing module (DSP). The DSP module processes collected light, temperature, and humidity data in real time, dynamically controlling the gain of different frequency bands. This allows the speaker's output sound to adapt to environmental changes, avoiding uneven sound quality caused by differences in light, temperature, and humidity. Through this adaptive gain adjustment and compensation, the smart speaker can provide a consistent and comfortable listening experience in a variety of lighting conditions, temperatures, and humidity environments, ensuring high-quality audio performance regardless of the user's environment.

[0143] Furthermore, when the ambient light intensity is lower than a preset threshold, the gain of the high frequency band of the audio signal is reduced; and the propagation attenuation of the audio signal is compensated according to the temperature and humidity data, including:

[0144] Monitors the ambient light intensity and compares it with a preset light threshold. When the light intensity is detected to be below the threshold, the high-frequency gain in the audio signal is reduced to reduce the irritation of the high-frequency sound to the user.

[0145] The propagation attenuation of the audio signal in the current environment is calculated based on the temperature and humidity data collected in real time, and the gain is adjusted based on the propagation attenuation to compensate for the sound attenuation in high humidity or low temperature environments.

[0146] In this embodiment, the smart speaker first monitors the light intensity in the environment in real time through the built-in light sensor. The system compares the detected light intensity data with a pre-set light threshold, which is usually the optimal range value for user comfort under different lighting conditions. When the light intensity is lower than the threshold, the smart speaker will recognize that the current environment is a dimly lit scene. In order to optimize the user experience, the system will automatically reduce the high-frequency gain in the audio signal to reduce the potential stimulation of high-frequency sounds to the user in a dark environment, thereby providing a softer and more comfortable listening effect. The reduction of the high-frequency gain can be achieved through digital signal processing (DSP). The system will apply a negative gain to the high-frequency component of the audio signal to reduce its output volume to avoid auditory fatigue in low-light environments.

[0147] At the same time, the smart speaker will also collect temperature and humidity data in the environment in real time. These data will affect the propagation characteristics of sound waves in the air. In high humidity or low temperature environments, changes in air density will lead to increased attenuation of sound waves, especially in the high frequency band. In order to ensure the balance of sound effects, the system will calculate the propagation attenuation of the audio signal in this environment based on the current temperature and humidity data. Generally, the propagation attenuation of sound waves can be expressed by a formula, which is related to factors such as air temperature, humidity, and pressure. In environments with low temperature or high humidity, the sound wave energy loss is relatively large. The system will compensate by adjusting the audio gain, increasing the output power of the high frequency band or the overall frequency band, and ensuring that the sound maintains a consistent listening experience under different temperature and humidity conditions.

[0148] This compensation process is also performed by the Digital Signal Processing (DSP) module. The system dynamically adjusts the gain of each frequency band based on the propagation attenuation calculated by temperature and humidity, ensuring that the speaker's audio output can adapt to changes in the environment. In this way, the smart speaker can achieve adaptive sound optimization under different lighting, temperature, and humidity conditions, providing users with a consistent and comfortable listening experience.

[0149] Step S107: performing spectrum analysis on the ambient noise data, generating a cancellation signal with a spectrum opposite to that of the ambient noise, and superimposing the signal onto the original audio signal to implement active noise reduction.

[0150] In step S107, the smart speaker collects ambient noise data through the built-in microphone system and performs spectrum analysis to identify the main frequency components and intensity distribution of the ambient noise. First, the speaker detects the noise in the surrounding environment through a multi-microphone array or a single high-sensitivity microphone to capture real-time audio data of the background noise. The captured data is subjected to spectrum analysis by the signal processing module, using spectrum analysis algorithms such as fast Fourier transform (FFT) to convert the time domain noise signal into a frequency domain signal. This can clearly distinguish the various frequency components of the ambient noise and their corresponding amplitudes, especially those stronger noise components that persist in the environment.

[0151] After obtaining the noise spectrum, the smart speaker generates a cancellation signal with an inverse spectrum to the ambient noise. The frequency, phase, and amplitude of this cancellation signal are precisely adjusted so that when superimposed on the ambient noise, it interferes with it and reduces its overall intensity. This cancellation signal generation is based on the inverse phase principle: the cancellation signal's phase is set opposite to that of the ambient noise, resulting in destructive interference when the two are superimposed. The speaker adjusts the amplitude of the cancellation signal based on the amplitude information of each major noise frequency band, making noise cancellation more effective during the active noise reduction process.

[0152] Next, the smart speaker superimposes the generated cancellation signal with the original audio signal. This superposition process is accomplished through the digital signal processing (DSP) module, ensuring that the cancellation signal is output synchronously with the original audio signal to achieve optimal noise reduction. To ensure the effectiveness of the cancellation signal across different frequency bands, the DSP module processes the noise reduction signal for each frequency band separately, allowing each frequency band to accurately reduce the corresponding noise during the speaker's sound production.

[0153] Through this active noise reduction process, the smart speaker effectively reduces background noise in the surrounding environment when outputting audio signals, especially low- and mid-frequency noise, making the music or audio content played clearer. In addition, this active noise reduction technology does not rely on external physical isolation. Instead, it uses spectrum analysis and phase cancellation principles to enable the smart speaker to achieve high-quality sound output even in complex environments, providing users with a purer and more immersive listening experience.

[0154] Furthermore, performing spectrum analysis on the ambient noise data to generate a cancellation signal having a spectrum opposite to that of the ambient noise, and superimposing the signal onto the original audio signal to achieve active noise reduction, includes:

[0155] Collect environmental noise data and perform real-time spectrum analysis to identify the main frequency bands of environmental noise;

[0156] Based on the spectrum result of the ambient noise, a cancellation signal with an opposite spectrum to the ambient noise is generated, where the signal has the same frequency and phase as the ambient noise but opposite amplitude to achieve effective noise cancellation;

[0157] The generated cancellation signal is superimposed on the original audio signal, and the interference of ambient noise is reduced through active noise reduction technology, thereby improving the sound clarity and sound quality output by the speaker.

[0158] In this embodiment, the smart speaker uses active noise reduction technology to reduce the interference of ambient noise on the audio output, thereby improving the clarity and sound quality of the sound. First, the microphone system of the smart speaker continuously collects ambient noise data to capture the surrounding background noise. These noise data are subjected to real-time spectrum analysis through the digital signal processing (DSP) module to decompose the main frequency components and amplitude information of the ambient noise. The spectrum analysis process may use technologies such as fast Fourier transform (FFT) to convert the noise signal from the time domain to the frequency domain, thereby identifying the main frequency bands of the ambient noise and the noise intensity in each frequency band.

[0159] After obtaining the spectral characteristics of the ambient noise, the system uses this information to generate a cancellation signal with an inverse spectrum to the ambient noise. This cancellation signal has the same frequency and phase as the ambient noise, but with an opposite amplitude. In other words, the cancellation signal maintains the same vibration pattern as the ambient noise across each major noise frequency band, but with the peaks and troughs in opposite directions. This design aims to cancel out the noise signal through the principle of destructive interference. When two signals with opposite amplitudes overlap in space, they cancel each other out, reducing the overall noise intensity. Generating the cancellation signal requires precise control of the signal's phase and amplitude to ensure optimal noise suppression across all frequency bands.

[0160] After generating the cancellation signal, the smart speaker superimposes it on the original audio signal. This superposition process is precisely controlled by the speaker's DSP module to ensure that the cancellation signal is output synchronously with the original audio signal, thus achieving effective active noise reduction. When the speaker plays audio, the output with the superimposed cancellation signal not only contains the original audio content but also includes a component specifically designed to cancel out ambient noise. In this way, the system can significantly reduce the interference of ambient noise, allowing users to clearly hear the speaker's output audio even in noisy environments.

[0161] This active noise cancellation feature is particularly suitable for smart speakers used in complex environments, such as indoors with background noise or in open spaces. It helps the speaker automatically adapt to environmental changes, providing a purer and more immersive listening experience. This technology achieves real-time adaptive noise suppression without manual user intervention, allowing smart speakers to maintain high-quality audio performance in various environments.

[0162] Furthermore, the performing of spectrum analysis on the ambient noise data to generate a cancellation signal having a spectrum opposite to that of the ambient noise, and superimposing the signal onto the original audio signal to achieve active noise reduction, further includes:

[0163] The amplitude and phase of the cancellation signal are dynamically adjusted according to changes in the ambient noise data to maintain the optimal noise reduction effect when the noise spectrum changes. An adaptive filtering algorithm is further applied to the cancellation signal to match the real-time characteristics of the ambient noise in different frequency bands, thereby achieving more accurate active noise reduction in multi-band complex noise environments.

[0164] In this embodiment, the smart speaker not only generates a cancellation signal opposite to the ambient noise spectrum through spectrum analysis, but also introduces a dynamic adjustment mechanism and adaptive filtering algorithm to further improve the accuracy and effect of active noise reduction.

[0165] First, the smart speaker continuously collects noise data from the environment and monitors the noise's spectral characteristics in real time. Because ambient noise is often dynamic, its frequency distribution and intensity can fluctuate significantly over time and space. Therefore, to maintain optimal noise reduction, the system dynamically adjusts the amplitude and phase of the cancellation signal based on changes in the detected noise data. Amplitude control of the cancellation signal ensures that the cancellation signal output increases accordingly as noise intensity increases, achieving sufficient noise reduction. Phase control ensures that the cancellation signal and the ambient noise are always in opposite phase, achieving destructive interference across different frequency bands. Through this dynamic adjustment, the system can promptly respond to changes in the ambient noise spectrum, ensuring that the cancellation signal effectively cancels the ambient noise at any given time.

[0166] Furthermore, the system applies an adaptive filtering algorithm to the cancellation signal, enabling it to match the real-time characteristics of the ambient noise across different frequency bands. This adaptive filtering algorithm is an intelligent signal processing method that iteratively learns the characteristics of the ambient noise, enabling more precise control of the cancellation signal across different frequency bands. This means the system can generate corresponding cancellation signals for the low, mid, and high frequency bands, ensuring precise phase matching and amplitude adjustment for the noise in each frequency band, thereby achieving optimized noise reduction across the entire frequency band.

[0167] In a complex multi-band noise environment, such as when traffic noise, background human voices, and other electronic equipment noise coexist, the adaptive filtering algorithm allows the system to perform noise reduction processing based on the noise characteristics of different frequency bands. Low-frequency traffic noise, mid-frequency human voices, and high-frequency electronic noise each have different spectral characteristics and attenuation characteristics. The adaptive filtering algorithm can adjust the amplitude and phase of the offset signal based on these characteristics to ensure that the noise in each frequency band can be processed in a targeted manner. Through this multi-band precise matching active noise reduction technology, the smart speaker can still provide clear sound quality and stable noise reduction effects in complex noise environments, allowing users to get a high-quality listening experience even in noisy environments.

[0168] Furthermore, the smart speaker audio enhancement method based on magnetic position and environmental characteristics further includes:

[0169] Providing a user interaction interface to the user, wherein the user interaction interface allows the user to adjust the reverberation time and reflection gain, the frequency band gain of the frequency response compensation curve, the phase difference and gain ratio of the sound unit, and the amplitude of the cancellation signal;

[0170] Detecting and recording parameter adjustment operations performed by the user through the user interaction interface;

[0171] Using a machine learning algorithm, the parameter adjustment operation is associated with the current magnetic adsorption position type and environmental feature data to establish a user sound effect preference model;

[0172] When a new magnetic adsorption position and environmental features are detected, they are input into the user sound preference model to predict the target audio processing parameters; and the target audio processing parameters are applied to the audio signal processing of the smart speaker.

[0173] In this embodiment, the smart speaker allows users to make detailed customized adjustments to the sound effects through a user interface. The user interface includes control options for a variety of parameters, such as reverberation time, reflection gain, frequency band gain of the frequency response compensation curve, phase difference and gain ratio of the sound unit, and amplitude of the cancellation signal in the active noise reduction function. Users can adjust these parameters through the user interface according to actual listening needs in different environments, such as when adsorbing on metal surfaces, glass surfaces or wall surfaces, to obtain the best listening effect. Each adjustment operation of the user will be monitored and recorded by the system in real time, and the system will associate the environmental data at the time of the operation, including the magnetic adsorption position type, adsorption angle, room size, furniture density, sound absorbing material distribution, temperature and humidity, and environmental noise data.

[0174] After recording the user's parameter adjustment operations, the smart speaker uses a machine learning algorithm to gradually build a user sound preference model. For example, when the user attaches the speaker to the wall surface and adjusts the reverberation time and reflection gain to adapt to the wall's reflective characteristics, the system will record the reverberation time parameters adjusted by the user and the corresponding magnetic adsorption position on the wall surface. In the multiple operations recorded by the system, if the user adjusts the reverberation time to a shorter value in a wall surface environment multiple times, the system can identify the user's preference pattern in this type of environment, that is, a tendency to reduce the reverberation time. This preference pattern, together with environmental data such as the wall surface, specific room size, and furniture density, forms a specific feature set. Based on this feature set, the system will input the operation data into the model for training through a supervised learning algorithm, thereby gradually capturing the user's adjustment patterns in this type of environment.

[0175] Specific machine learning algorithms can use algorithms such as decision trees or random forests. Decision tree algorithms can establish a regularized logical relationship between the input environmental characteristics and the user's sound preferences. For example, the model may learn that users tend to increase the gain in the high-frequency band when adsorbing on a metal surface, and tend to increase the reverberation time in an environment with less sound-absorbing materials. Every time a user adjusts a parameter, the system records these adjustments along with the environmental characteristic data as training samples. As the number of users uses the smart speaker increases, the smart speaker gradually accumulates operational data in different environments, and the amount of training data continues to increase. The model can gradually summarize the user's sound preference patterns in various environments.

[0176] After the user sound preference model is basically formed, when the smart speaker is placed in a new magnetic adsorption position or detects changes in environmental characteristics, the system will automatically call the user sound preference model, use the new position and new environmental characteristics as input, and predict the target audio processing parameters suitable for the current environment. For example, assuming that the user speaker is moved from the glass surface to the wall surface, and the furniture density in the room is high and the sound-absorbing material covers a wide area, the system can refer to the user preference model to predict the reverberation time and frequency band gain adjustment values ​​required in this environment. Based on historical data, the model will infer that the user may need to reduce the reverberation time and increase the low-frequency gain to counteract the attenuation effect of the sound-absorbing material. In this way, the system can automatically apply the user's preferences in different environments, thereby realizing automatic sound adjustment and providing users with a consistent listening experience.

[0177] A second embodiment of the present application provides an electronic device, comprising:

[0178] processor;

[0179] The memory is used to store a program, which, when read and executed by the processor, executes a smart speaker audio enhancement method based on magnetic position and environmental characteristics provided in the first embodiment of the present application.

[0180] The third embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the smart speaker audio enhancement method based on magnetic position and environmental characteristics provided in the first embodiment of the present application is executed.

[0181] Although the present application is disclosed as above with the preferred embodiments, it is not intended to limit the present application. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

Claims

1. A smart speaker audio enhancement method based on magnetic position and environmental characteristics, characterized in that: include: Detecting the current magnetic adsorption position type and magnetic adsorption angle of the smart speaker, and collecting environmental feature data and ambient noise data around the smart speaker; wherein the magnetic adsorption position types include metal planes, glass surfaces, wall surfaces, and furniture surfaces with metal frames; the environmental feature data includes room size, furniture density, sound-absorbing material distribution, ambient light intensity, and ambient temperature and humidity; Determining the material characteristics of the reflective surface according to the magnetic adsorption position type; Calculating a sound wave reflection path based on the material properties of the reflective surface, the room size, and the furniture density; adjusting the reverberation time and reflection gain of the audio signal based on the sound wave reflection path to generate a sound diffusion pattern adapted to the current space; and reconstructing the spatial sound field of the input audio signal using the sound diffusion pattern; Based on the distribution of the sound absorbing material, different frequency bands of the audio signal are compensated to generate a frequency response compensation curve, wherein the compensation curve is used to enhance the frequency band attenuated by the sound absorbing material; Calculating the radiation path of the sound wave in space according to the magnetic adsorption angle; and adjusting the phase difference and gain ratio of each sound unit of the speaker according to the radiation path to achieve a directional sound field; When the ambient light intensity is lower than a preset threshold, the gain of the high frequency band of the audio signal is reduced; and the propagation attenuation of the audio signal is compensated according to the temperature and humidity data; The ambient noise data is subjected to spectrum analysis to generate a cancellation signal having a spectrum opposite to that of the ambient noise, and the cancellation signal is superimposed on the original audio signal to achieve active noise reduction.

2. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1 is characterized in that: Also includes: Providing a user interaction interface to the user, wherein the user interaction interface allows the user to adjust the reverberation time and reflection gain, the frequency band gain of the frequency response compensation curve, the phase difference and gain ratio of the sound unit, and the amplitude of the cancellation signal; Detecting and recording parameter adjustment operations performed by the user through the user interaction interface; Using a machine learning algorithm, the parameter adjustment operation is associated with the current magnetic adsorption position type and environmental feature data to establish a user sound effect preference model; When a new magnetic adsorption position and environmental features are detected, they are input into the user sound preference model to predict the target audio processing parameters; and the target audio processing parameters are applied to the audio signal processing of the smart speaker.

3. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1 is characterized in that: The detecting the current magnetic adsorption position type and magnetic adsorption angle of the smart speaker and collecting environmental feature data and environmental noise data around the smart speaker include: Use multiple sensors to detect the smart speaker's magnetic adsorption location type in real time, determining whether the speaker is currently adsorbed on a metal surface, glass surface, wall surface, or furniture with a metal frame; The angle sensor is used to obtain the current magnetic adsorption angle of the smart speaker and record the tilt angle of the speaker relative to the horizontal plane. Collect characteristic data of the speaker's surrounding environment, including room size, furniture density, distribution of sound-absorbing materials, ambient light intensity, and temperature and humidity parameters, as well as obtain noise data in the current environment; The collected environmental feature data and magnetic adsorption position type information are stored in a storage module of the speaker.

4. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: The determining of the material characteristics of the reflective surface according to the magnetic adsorption position type includes: Metal planes correspond to high reflectivity acoustic properties; Glass surfaces correspond to medium reflectivity acoustic properties; The wall surface corresponds to low reflectivity acoustic properties; Furniture surfaces with metal frames correspond to mixed reflectivity acoustic properties.

5. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: The method comprises calculating a sound wave reflection path by combining the material characteristics of the reflecting surface, the room size, and the furniture density; adjusting the reverberation time and reflection gain of the audio signal according to the sound wave reflection path to generate a sound diffusion pattern adapted to the current space; and reconstructing the spatial sound field of the input audio signal using the sound diffusion pattern, including: Analyze the propagation characteristics of sound waves in the room, including reflection, absorption, and scattering paths, based on the material properties of the reflective surface, the size of the room, and the density of furniture; Adjust the reverberation time of the audio signal according to the sound wave reflection path to ensure that the sound output by the speaker has adaptive sound performance on different reflection surfaces; By adjusting the reflection gain and optimizing the sound diffusion pattern, the sound effect is made more uniform at different locations in the room, and the sound diffusion pattern is used to reconstruct the spatial sound field of the input audio signal to adapt to the spatial characteristics of the current room.

6. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: The method calculates the radiation path of the sound wave in space according to the magnetic adsorption angle; and adjusts the phase difference and gain ratio of each sound unit of the speaker according to the radiation path to achieve a directional sound field, including: According to the following formula 1, the weighted path length L required for the composite propagation path of the sound waves emitted by the smart speaker to the target listening area in the room is calculated: w : Among them, L i is the propagation distance of the sound wave in the i-th segment of the reflection path; μ is the air attenuation coefficient; α is the angle between the sound wave in the i-th segment of the path and the reflecting surface; N is the maximum number of reflections; α0 is the initial radiation angle, calculated by the following formula 2: Where θ is the magnetic adsorption angle of the smart speaker; h is the height of the magnetic adsorption position; d is the horizontal distance between the speaker and the main reflective surface; The phase difference Δφ of the sound unit is determined according to the following formula 3: Where λ is the wavelength of the sound wave; θ is the magnetic adsorption angle of the smart speaker; L w is the weighted path length required for the complex propagation path of the sound wave in the room; The gain ratio G of the sound unit is determined according to the following formula 4: Among them, A is the sound intensity coefficient; L w is the weighted path length required for the complex propagation path of the sound wave in the room; μ is the air attenuation coefficient.

7. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: The method of compensating different frequency bands of the audio signal based on the distribution of the sound absorbing material to generate a frequency response compensation curve, wherein the compensation curve is used to enhance the frequency band attenuated by the sound absorbing material, includes: Get the coordinates of each sound-absorbing material area in the room (x i ,y i , z i ) and the sound absorption coefficient α of each area i (f), where α i (f) represents the absorption coefficient of the i-th sound absorption area at the target frequency f; The weighted average absorption coefficient is calculated according to the following formula 5: Among them, α weighted (f, θ) is the weighted average sound absorption coefficient; N is the total number of sound absorbing material areas; S i is the surface area of ​​the i-th sound-absorbing material area; S total is the total surface area of ​​the room; θ is the magnetic adsorption angle of the smart speaker; β is the distance attenuation coefficient of the absorption coefficient; d i (θ) is the distance between the magnetic adsorption position of the smart speaker and the i-th sound-absorbing material area, and is calculated using the following formula 6: Among them, (x, y, z) is the magnetic adsorption position coordinate of the smart speaker; (x i ,y i , z i ) is the coordinate of the i-th sound absorbing material area; The frequency response compensation coefficient is calculated according to the following formula 7: Where C(f, θ) is the frequency response compensation coefficient; k is the compensation intensity adjustment coefficient; θ0 is the reference angle, which is the main direction angle of the speaker sound; The enhanced gain G(f) is generated according to the following formula 8: G(f)=G base (f)·C(f,θ) (8) Among them, G base (f) is the initial gain at the target frequency f.

8. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: When the ambient light intensity is lower than a preset threshold, reducing the gain of the high frequency band of the audio signal; And compensate for the propagation attenuation of the audio signal based on the temperature and humidity data, including: Monitors the ambient light intensity and compares it with a preset light threshold. When the light intensity is detected to be below the threshold, the high-frequency gain in the audio signal is reduced to reduce the irritation of the high-frequency sound to the user. The propagation attenuation of the audio signal in the current environment is calculated based on the temperature and humidity data collected in real time, and the gain is adjusted based on the propagation attenuation to compensate for the sound attenuation in high humidity or low temperature environments.

9. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: The performing spectrum analysis on the ambient noise data to generate a cancellation signal opposite to the ambient noise spectrum, and superimposing the signal onto the original audio signal to achieve active noise reduction, includes: Collect environmental noise data and perform real-time spectrum analysis to identify the main frequency bands of environmental noise; Based on the spectrum result of the ambient noise, a cancellation signal with an opposite spectrum to the ambient noise is generated, where the signal has the same frequency and phase as the ambient noise but opposite amplitude to achieve effective noise cancellation; The generated cancellation signal is superimposed on the original audio signal, and the interference of ambient noise is reduced through active noise reduction technology, thereby improving the sound clarity and sound quality output by the speaker.

10. The smart speaker audio enhancement method based on magnetic position and environmental characteristics according to claim 1, characterized in that: The performing spectrum analysis on the ambient noise data to generate a cancellation signal opposite to the ambient noise spectrum, and superimposing the cancellation signal onto the original audio signal to achieve active noise reduction, further includes: The amplitude and phase of the cancellation signal are dynamically adjusted according to changes in the ambient noise data to maintain the optimal noise reduction effect when the noise spectrum changes. An adaptive filtering algorithm is further applied to the cancellation signal to match the real-time characteristics of the ambient noise in different frequency bands, thereby achieving more accurate active noise reduction in multi-band complex noise environments.

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