Sound scene enhancement device based on environmental perception

Abstract

The utility model discloses a sound scene enhancing device based on environmental perception, and relates to the technical field of acoustics. The system comprises a microphone array, a signal conditioning circuit, an analog-to-digital converter, a DSP processor, a sound scene database memory, a master control MCU, an FPGA beam controller, an audio synthesis chip, a power amplifier, a loudspeaker array and a noise classification coprocessor, the microphone array is electrically connected with the signal conditioning circuit, and the signal conditioning circuit is electrically connected with the analog-to-digital converter. The analog-to-digital converter is electrically connected with the DSP processor, the analog-to-digital converter is electrically connected with the master control MCU, the DSP processor is electrically connected with the sound scene database memory, the DSP processor is electrically connected with the noise classification coprocessor, the noise classification coprocessor is electrically connected with the master control MCU, the master control MCU is electrically connected with the sound scene database memory, and the master control MCU is electrically connected with the FPGA beam controller. The sound scene can be automatically adjusted according to environment changes.

Description

TECHNICAL FIELD

[0001] The utility model relates to acoustics technical field especially relates to a kind of soundscape enhancement device based on environmental perception. BACKGROUND

[0002] With the acceleration of urbanization, noise pollution has become an important factor affecting people's quality of life. Traditional noise control methods, such as soundproof walls, sound-absorbing materials, etc., although reduce noise level to some extent, often overlook the overall quality of the sound environment, resulting in a single sound scene and lack of vitality. Soundscape enhancement technology aims to improve the sound environment and enhance people's auditory experience by introducing natural sounds, music and other beneficial sounds. However, existing soundscape enhancement devices lack real-time environmental noise perception and dynamic response capabilities, and cannot automatically adjust the soundscape according to environmental changes, limiting their application effectiveness and user experience.

[0003] The existing soundscape enhancement device cannot automatically adjust the soundscape according to environmental changes, which is a technical problem to be solved. UTILITY MODEL CONTENT

[0004] The utility model provides a kind of soundscape enhancement device based on environmental perception, solves the technical problem that cannot automatically adjust the soundscape according to environmental changes.

[0005] To solve the above technical problems, the technical solution adopted by the utility model is as follows:

[0006] A soundscape enhancement device based on environmental perception includes a microphone array, a signal conditioning circuit, an analog-to-digital converter, a DSP processor, a soundscape database storage, a main control MCU, a FPGA beam controller, an audio synthesis chip, a power amplifier, a loudspeaker array, and a noise classification coprocessor. The microphone array is electrically connected to the signal conditioning circuit. The signal conditioning circuit is electrically connected to the analog-to-digital converter. The analog-to-digital converter is electrically connected to the DSP processor. The analog-to-digital converter is electrically connected to the main control MCU. The DSP processor is electrically connected to the soundscape database storage. The DSP processor is electrically connected to the noise classification coprocessor. The noise classification coprocessor is electrically connected to the main control MCU. The main control MCU is electrically connected to the soundscape database storage. The main control MCU is electrically connected to the FPGA beam controller. The audio synthesis chip is electrically connected to the FPGA beam controller. The FPGA beam controller is electrically connected to the power amplifier. The power amplifier is electrically connected to the loudspeaker array.

[0007] Further technical solutions include a touch screen electrically connected to the main control MCU.

[0008] Further technical solutions include that the touch screen is a capacitive touch screen.

[0009] Further technical solutions are that the microphone array is connected with the signal conditioning circuit through a shielded cable and communicates unidirectionally, the signal conditioning circuit is connected with the analog-to-digital converter through an SPI bus and communicates unidirectionally, the analog-to-digital converter is connected with the DSP processor through an SPI bus and communicates unidirectionally, the analog-to-digital converter is connected with the master MCU through an I2C bus and communicates unidirectionally, the DSP processor is connected with the sound scene database memory through an I2C bus and communicates unidirectionally, the DSP processor is connected with the noise classification coprocessor through an I2C bus and communicates unidirectionally, and the noise classification coprocessor is connected with the master MCU through an I2C bus and communicates unidirectionally.

[0010] Further technical solutions are that the master MCU is connected with the sound scene database memory through an SDIO interface and communicates unidirectionally, the master MCU is connected with the capacitive touch screen through a UART interface and communicates bidirectionally, the master MCU is connected with the FPGA beam controller through a GPIO interface and communicates unidirectionally, the audio synthesis chip is connected with the FPGA beam controller through a GPIO interface and communicates unidirectionally, the FPGA beam controller is connected with the power amplifier through a PWM interface and communicates unidirectionally, and the power amplifier is connected with the loudspeaker array and communicates unidirectionally.

[0011] The above technical solutions have the following beneficial effects:

[0012] A sound scene enhancement device based on environmental perception includes a microphone array, a signal conditioning circuit, an analog-to-digital converter, a DSP processor, a sound scene database memory, a master MCU, an FPGA beam controller, an audio synthesis chip, a power amplifier, a loudspeaker array and a noise classification coprocessor, the microphone array is electrically connected with the signal conditioning circuit, the signal conditioning circuit is electrically connected with the analog-to-digital converter, the analog-to-digital converter is electrically connected with the DSP processor, the analog-to-digital converter is electrically connected with the master MCU, the DSP processor is electrically connected with the sound scene database memory, the DSP processor is electrically connected with the noise classification coprocessor, the noise classification coprocessor is electrically connected with the master MCU, the master MCU is electrically connected with the sound scene database memory, the master MCU is electrically connected with the FPGA beam controller, the audio synthesis chip is electrically connected with the FPGA beam controller, the FPGA beam controller is electrically connected with the power amplifier, and the power amplifier is electrically connected with the loudspeaker array. Through the microphone array, the signal conditioning circuit, the analog-to-digital converter, the DSP processor, the sound scene database memory, the master MCU, the FPGA beam controller, the audio synthesis chip, the power amplifier, the loudspeaker array and the noise classification coprocessor, the sound scene can be automatically adjusted according to environmental changes. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 It is a principle block diagram of the utility model. DETAILED DESCRIPTION

[0014] The purpose of the present application is to provide an environment-aware soundscape enhancement device, which can monitor environmental noise in real time, intelligently analyze noise characteristics, and dynamically generate and play appropriate soundscape according to the analysis results, thereby effectively improving the quality of the sound environment and enhancing the auditory comfort of people.

[0015] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and in no way limits the present application and its applications or uses. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0016] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0017] As Figure 1 The utility model discloses an environment-aware soundscape enhancement device, which comprises a microphone array, a signal conditioning circuit, an analog-to-digital converter, a DSP processor, a soundscape database storage, a main control MCU, a capacitive touch screen, an FPGA beam controller, an audio synthesis chip, a power amplifier, a loudspeaker array and a noise classification coprocessor. The microphone array is connected with the signal conditioning circuit through a shielding cable and communicates unidirectionally. The signal conditioning circuit is connected with the analog-to-digital converter through an SPI bus and communicates unidirectionally. The analog-to-digital converter is connected with the DSP processor through an SPI bus and communicates unidirectionally. The analog-to-digital converter is connected with the main control MCU through an I2C bus and communicates unidirectionally. The DSP processor is connected with the soundscape database storage through an I2C bus and communicates unidirectionally. The DSP processor is connected with the noise classification coprocessor through an I2C bus and communicates unidirectionally. The noise classification coprocessor is connected with the main control MCU through an I2C bus and communicates unidirectionally. The main control MCU is connected with the soundscape database storage through an SDIO interface and communicates unidirectionally. The main control MCU is connected with the capacitive touch screen through a UART interface and communicates bidirectionally. The main control MCU is connected with the FPGA beam controller through a GPIO interface and communicates unidirectionally. The audio synthesis chip is connected with the FPGA beam controller through a GPIO interface and communicates unidirectionally. The FPGA beam controller is connected with the power amplifier through a PWM interface and communicates unidirectionally. The power amplifier is connected with the loudspeaker array and communicates unidirectionally.

[0018] The microphone array is installed with four microphones on a 150mmX150mm PCB board, and the speaker array is composed of six speakers.

[0019] The model of the microphone array is WM-61A x 4, the model of the analog-to-digital converter is ADS1278, the model of the DSP processor is TMS320C6748, the model of the sound scene database memory is SanDisk 64GB TF, the model of the main control MCU is STM32H743, the model of the 7-inch capacitive touch screen is RA8875, the model of the audio synthesis chip is CSRA64215, the model of the FPGA beam controller is Artix-7, the model of the power amplifier is TPA3255, the model of the speaker array is JBL Control 25-1 x 6, and the model of the noise classification coprocessor is Raspberry Pi CM4. The connection relationship between each device is shown in Table 1.

[0020] Table 1: Device and data transfer logic table

[0021]

[0022] The environmental noise collection unit is composed of a high-sensitivity microphone array, a signal conditioning circuit, and an analog-to-digital converter. The microphone array uses omnidirectional or directional microphones and is arranged at multiple positions in the target area for omnidirectional collection of noise signals in the environment. The signal conditioning circuit amplifies and filters the collected analog signals, and the analog-to-digital converter converts the analog signals into digital signals and transmits them to the noise analysis unit.

[0023] The noise analysis unit includes a digital signal processor (DSP) and a noise feature extraction algorithm. The digital signal processor processes the received noise signals in real time, including fast Fourier transform (FFT) to obtain the noise spectrum, sound pressure level calculation to evaluate the noise intensity, and noise source identification algorithms such as machine learning-based classification models to determine the noise type, such as traffic noise, construction noise, human voice, etc. The noise feature extraction algorithm further analyzes the time characteristics, frequency characteristics, and spatial distribution of the noise to provide data support for sound scene generation. The noise analysis unit and the algorithms therein are existing technologies and will not be described in detail.

[0024] Soundscapes generation unit: composed of soundscapes database storage and audio synthesis chip. The soundscapes database stores various types of soundscapes materials, such as natural sounds, music clips or white noise, natural sounds including bird songs, running water, wind sounds, etc. The soundscapes synthesis algorithm selects or synthesizes appropriate soundscapes signals from the database in real time according to the noise characteristics provided by the noise analysis unit. For example, for high-frequency traffic noise, low-frequency natural sound can be generated to mask the noise; for intermittent construction noise, continuous soothing music can be generated to distract attention. The audio synthesis chip processes the generated soundscapes signals for equalization, reverb, etc. to optimize sound quality and spatial sense. Noise type and soundscapes parameter mapping table, see Table 2.

[0025] Table 2: Noise type and soundscapes parameter mapping table

[0026]

[0027] The noise type and soundscapes parameter mapping table is stored in the Flash of the main control MCU.

[0028] Audio playback unit: including power amplifier, speaker array and FPGA beam controller. The power amplifier amplifies the audio signals output by the soundscapes generation unit to an appropriate level. The speaker array is composed of multiple speaker units, arranged at reasonable positions in the target area, for playing soundscapes signals. The FPGA beam controller realizes the directional propagation of soundscapes signals by adjusting the phase and amplitude of each speaker unit, ensuring that the soundscapes enhancement effect is concentrated in the target area, reducing the interference to the surrounding environment.

[0029] Control unit: realized by the main control MCU, i.e. microprocessor or embedded system, responsible for coordinating the workflow of each unit. The control unit receives data from the noise analysis unit, calls existing algorithms of the soundscapes generation unit, controls the operation of the audio playback unit, and supports user interaction functions. In addition, the control unit can also integrate network communication units such as Wi-Fi, Bluetooth, to realize remote control and data sharing.

[0030] User interaction unit: including touch screen, mobile application or voice assistant, providing an intuitive operation interface for users. Users can view environmental noise data in real time, select preset soundscapes modes such as forest mode, beach mode, adjust soundscapes volume or customize personalized soundscapes through this module. The user interaction unit can also optimize soundscapes generation strategies according to user feedback to improve user experience.

[0031] Environmental adaptive adjustment example, hardware response process as follows.

[0032] Scenario: traffic noise is detected, and a 63Hz peak is identified by the DSP processor.

[0033] 1. Data trigger: microphone array → ADC → DSP outputs spectral features 63Hz proportion > 30% co-processor → MCU returns label traffic noise.

[0034] 2. Hardware response: master MCU reads Table 2 from Flash, sends instructions: soundscapes memory address 0x0012, i.e. water sound material, audio synthesis chip register configures EQ parameters 0x1A, FPGA beam controller phase delay code 0x3F corresponds to horizontal direction ±10°.

[0035] 3. Effect verification: loudspeaker array outputs water sound, measured noise masking amount ≥ 8dB, sound level meter data.

[0036] Compared with the prior art, the application has the beneficial technical effects as follows.

[0037] First, real-time noise perception and dynamic response: through a high-sensitivity microphone array, real-time acquisition of environmental noise signals is realized, and digital signal processing technology such as fast Fourier transform is used for frequency spectrum analysis and sound pressure level measurement of noise. The noise analysis unit can identify noise types such as traffic noise, construction noise, human voice, etc., and extract the time characteristics and spatial distribution characteristics of the noise. Based on these data, the sound scene generation strategy is dynamically adjusted to ensure that the sound scene signal is real-time matched with the environmental noise. For example, when high-frequency traffic noise is detected, low-frequency natural sound such as water sound will be automatically generated to mask the noise; when intermittent construction noise is detected, continuous soothing music will be played to distract the user's attention.

[0038] Second, intelligent sound scene generation and noise masking: the sound scene generation unit selects or synthesizes appropriate sound scene signals from the preset sound scene database according to the noise characteristics provided by the noise analysis unit. The sound scene database contains various natural sounds and music clips, which can generate customized sound scenes for different noise types, such as bird songs, wind sounds, and ocean wave sounds. For low-frequency mechanical noise, high-frequency natural sound such as bird song will be generated to form auditory contrast; for high-frequency traffic noise, low-frequency natural sound such as water sound will be generated to achieve spectral complementation. In addition, the sound scene generation unit also supports dynamically adjusting the volume, pitch and spatial sense of the sound scene signal to optimize the masking effect.

[0039] Third, directional sound scene playback and regional focus: The audio playback unit uses beamforming technology to adjust the phase and amplitude of each unit in the speaker array to direct the sound scene signal to the target area. For example, in an open office area, soothing music can be directed to the work area, while avoiding interference with the conference area or rest area; in the park, natural sounds such as bird songs can be directed to the tourist gathering area, while reducing the impact on the surrounding residential area. The FPGA beam controller also supports dynamic adjustment of the coverage range and sound pressure level of the sound scene to adapt to different scene requirements.

[0040] Fourth, user individualized experience and adaptive optimization: By equipping user interaction units such as touch screens and mobile applications, users can choose sound scene modes according to personal preferences, such as forest mode, beach mode, adjust volume, or customize individualized sound scenes. For example, users can choose to play focused music when working and relaxing natural sounds when resting. In addition, through machine learning algorithms to record user preferences and environmental noise change patterns, automatically optimize sound scene generation strategies. For example, if a user selects a certain type of sound scene multiple times, similar sound scenes will be preferentially recommended; if the characteristics of the environmental noise change, the sound scene generation parameters will be dynamically adjusted.

[0041] Fifth, multi-scene applicability and green energy saving: It can be widely used in office buildings, residential areas, parks, hospitals, libraries and other scenes. For example, in office buildings, it can reduce the interference of keyboard tapping and telephone ringing; in residential areas, it can mask traffic noise and construction noise; in hospitals, it can play soothing music to relieve patient anxiety. In addition, it can be equipped with solar panels or energy recovery systems to use environmental light energy or sound energy to power it, reducing energy consumption and achieving green and environmentally friendly operation.

Claims

1. An environment-aware sound scene enhancement device, characterized by: The application relates to a sound field synthesis device, which comprises a microphone array, a signal conditioning circuit, an analog-to-digital converter, a DSP processor, a sound field database memory, a main control MCU, an FPGA beam controller, an audio synthesis chip, a power amplifier, a loudspeaker array and a noise classification coprocessor.

2. The soundscape enhancement device based on environmental perception according to claim 1, characterized in that: The main control MCU is electrically connected with a touch screen.

3. The sound scene enhancement device based on environmental perception according to claim 2, characterized in that: The touch screen is a capacitive touch screen.

4. The sound scene enhancement device based on environmental perception according to claim 1, characterized in that: The microphone array is connected with the signal conditioning circuit through a shielded cable and communicates unidirectionally, the signal conditioning circuit is connected with the analog-to-digital converter through an SPI bus and communicates unidirectionally, the analog-to-digital converter is connected with the DSP processor through an SPI bus and communicates unidirectionally, the analog-to-digital converter is connected with the main control MCU through an I2C bus and communicates unidirectionally, the DSP processor is connected with the sound field database memory through an I2C bus and communicates unidirectionally, the DSP processor is connected with the noise classification coprocessor through an I2C bus and communicates unidirectionally, and the noise classification coprocessor is connected with the main control MCU through an I2C bus and communicates unidirectionally.

5. The sound scene enhancement device based on environmental perception according to claim 1, characterized in that: The main control MCU is connected with the sound field database memory through an SDIO interface and communicates unidirectionally, the main control MCU is connected with the capacitive touch screen through a UART interface and communicates bidirectionally, the main control MCU is connected with the FPGA beam controller through a GPIO interface and communicates unidirectionally, the audio synthesis chip is connected with the FPGA beam controller through a GPIO interface and communicates unidirectionally, the FPGA beam controller is connected with the power amplifier through a PWM interface and communicates unidirectionally, and the power amplifier is connected with the loudspeaker array and communicates unidirectionally.

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