401 results about "Acoustic source localization" patented technology

The invention relates to a microphone array sound source positioning method and system based on cross-correlation-beam forming closed-loop optimization, and belongs to the technical field of sound source positioning. The method comprises the following steps: collecting multichannel sound signals through a microphone array and preprocessing the multichannel sound signals to extract time-frequency features and suppress noise interference; time delay information among the microphones is estimated by adopting a generalized cross-correlation phase transformation algorithm, and an optimization strategy is introduced to improve estimation stability and anti-interference performance; enhancing the target sound source signal in combination with a minimum variance undistorted response beam forming algorithm and an adaptive Kalman filtering mechanism; constructing a closed-loop feedback optimization mechanism based on the beam output signal to realize feedback adjustment; and adopting a hybrid network architecture, taking the beam output signal amplitude spectrum as input, and outputting the frequency spectrum or mask of the obtained target sound source signal. The method has the advantages of high calculation efficiency, high positioning precision and strong anti-interference capability, and is suitable for real-time acoustic signal processing in a complex environment.

The invention relates to the technical field of submarine cable fault positioning, in particular to a submarine cable fault positioning system based on underwater beacons. The method comprises the steps that an underwater acoustic beacon array unit monitors and collects submarine cable fault sound wave signals in real time based on underwater acoustic beacons; the fault signal processing analysis unit extracts submarine cable fault sound wave signal parameters based on a non-point source space sound source waveform analysis model, and generates multi-parameter fault sound source feature vectors; the sound source positioning analysis algorithm unit performs three-dimensional inversion positioning based on the multi-parameter fault sound source feature vector and the arrival time difference of the submarine cable fault sound wave signal to the underwater acoustic beacon, and obtains the spatial position information of the submarine cable fault point; and the data communication alarm management unit sends the spatial position information of the submarine cable fault point to a shore-based operation and maintenance system. The submarine cable fault positioning method is used for realizing a submarine cable fault positioning technology for quickly and accurately positioning and identifying spatial extension characteristics in a complex submarine environment.

The invention relates to the technical field of voice recognition, in particular to an implementation method and device of a multi-channel voiceprint recognition system, and the implementation method comprises the steps of multi-channel data acquisition and synchronization, signal preprocessing and enhancement, feature extraction and fusion, model training, real-time deployment and adaptive optimization. Compared with the problems that a traditional multichannel voiceprint recognition system depends on a fixed beam forming algorithm and an independent clock synchronization module, the synchronization error is large, manual parameter adjustment is needed for noise suppression, and generalization is poor, hardware-level clock synchronization is achieved through a PTP protocol, and the accuracy of noise suppression is improved. The method combines an end-to-end neural network to automatically learn noise distribution and a sound source space position, dynamically generates a beam forming weight, can improve the voice quality in a complex noise scene without manual intervention, remarkably reduces the interference of a synchronization error on sound source positioning, and enables the precision and stability of far-field voice enhancement to reach a new level.

The invention discloses an all-weather sound source positioning system and method based on multi-sensor fusion, and the method comprises the steps: firstly, obtaining acoustic sensing data, millimeter wave radar data and infrared thermal imaging data, and enabling each data to have a collection timestamp; then, cross-modal time alignment processing is carried out on the multi-source data to map the multi-source data to a unified time reference, and multi-modal fusion features under a unified time axis are obtained; for each time point in the time-aligned multi-modal fusion features, according to the confidence coefficient of the data of each sensor, adaptive weighted fusion is carried out on the data of different modals, and fused common feature representation is generated; and finally, time sequence modeling and joint reasoning are carried out based on the common feature representations of a plurality of continuous time points, and continuous position information of the sound source in the three-dimensional space is regressed. According to the method, high-precision positioning of three-dimensional positions of a plurality of sound sources is realized, so that the accuracy and the stability of sound source positioning are improved in a complex environment and an all-weather condition.

The invention relates to the technical field of environmental noise monitoring, and discloses a road traffic noise intelligent monitoring and three-dimensional sound field reconstruction system, which comprises an acoustic sensor module, a data collection and storage module, a data analysis and evaluation module, a three-dimensional sound field construction and display module and a traffic flow feature library. According to the system, a differential geometry principle is adopted, a sound field is regarded as a Riemannian manifold with a local microstructure, and accurate description of an irregular sound field is realized through a curvature self-adaptive sound field manifold construction technology; introducing a covariant derivative in Riemannian geometry, and constructing a sound propagation model adapted to a complex road environment; and realizing hierarchical decomposition and reconstruction of the sound field by using a multi-scale analysis theory. According to the method, the sound source positioning precision and the calculation efficiency are improved, seamless analysis from microcosmic to macroscopic is realized, an innovative solution is provided for traffic and noise collaborative management, and intelligent traffic and environmental noise management are effectively supported.

The invention relates to the field of real-time translation, and provides a real-time duplex translation method based on multichannel parallel processing and a corresponding product, and the method comprises the steps: collecting multipath voice signals of at least two user groups in real time through a group of audio collection modules; dynamically adjusting beam forming parameters of each audio acquisition module in one group of audio acquisition modules based on a sound source positioning result, and feeding back the beam forming parameters to the corresponding audio acquisition modules; monitoring the voice activity of each audio acquisition module corresponding to each audio channel; when it is monitored that the voice activity of any audio channel reaches a preset condition, automatically activating the translation processing flow of the audio channel and keeping the monitoring state of the other audio channels; a parallel processing mechanism is adopted for voice signals of the activated audio channels, and meanwhile real-time translation of the currently activated audio channels and voice activity monitoring of the other audio channels are executed; and transmitting a translation result of the current speaking user to other users participating in dialogue in the user group to realize synchronous coordination of multichannel data.

The invention discloses a spatial projection regularization method for sound source localization and sound field reconstruction and a related device, and belongs to the technical field of sound source localization. Specifically, according to the method, an equivalent source method model is utilized, and an external radiation sound field of a sound source to be measured is simulated through a series of virtual sources. Then, according to the first sound pressure transfer matrix from the virtual source arrangement surface to the holographic measuring point plane and the sound pressure of the holographic measuring point, a space projection regularization algorithm is used for solving the inverse problem, and therefore the equivalent source intensity is obtained; and then, reconstructing an external radiation sound field of the sound source to be detected by using the second sound pressure transfer matrix and the equivalent source intensity. And finally, by taking the maximum sound pressure amplitude as a standard, screening field points in an external radiation sound field so as to determine the position of the sound source to be detected. According to the space projection regularization algorithm, truncation processing of the vector space is carried out with the projection size of the measurement information in the vector space as the criterion, real information is reserved, and noise interference is restrained to the maximum extent.

Acoustic signals from an acoustic event are captured via sensing nodes of sensor group(s) that comprise a group of sensing nodes at a location comprising spatial boundaries. Each of the sensing nodes comprise a sensor area. Each of the sensor group(s) is based on: range limits of each of the sensing nodes; shared sensing areas of the sensing nodes; and intersections between the sensor area for each of the sensing nodes and the spatial boundaries. Solutions(s) are generated by processing the acoustic signals. The solution(s) indicate the location or trajectory of the acoustic event. A strength of solution compliance value for at least one of the solution(s) is determined. A refined solution is generated employing: sensor contributions of sensing nodes; and the strength of solution compliance value with the spatial boundaries and at least one of the solution(s). A report is created comprising the location or trajectory of the acoustic event.

The invention relates to a transformer abnormal sound source positioning method and system, and belongs to the technical field of power equipment state evaluation, and the method comprises the steps: constructing a Bayesian neural network embedded with a voiceprint physical mechanism, and enabling a sound wave propagation equation to serve as a physical constraint to be embedded into the Bayesian neural network; reconstructing the voiceprint signal by adopting a compressed sensing technology to obtain a reconstructed voiceprint field; designing a multi-task objective function including data fitting, physical constraint and positioning loss, and optimizing data fitting, physical constraint and positioning precision to obtain a trained Bayesian neural network; based on a gradient sound source inversion positioning algorithm and the trained Bayesian neural network, sparse regularization is combined to obtain a prediction result of accurate positioning; and a prediction result is visualized to a three-dimensional model of the transformer, and the position of an abnormal sound source is visually displayed. According to the method, the limitation of a traditional method in a complex environment is overcome, and high-precision and high-robustness transformer abnormal sound source positioning is realized.

The invention discloses a sound source localization method based on multi-frequency separation and Newton optimization deconvolution, relates to the technical field of array acoustic signal processing, and is used for solving the problem that weak sound sources and multiple sound sources are difficult to identify. According to the method, dominant frequency is extracted through multichannel frequency domain analysis, a cross-spectrum matrix is constructed in combination with a near-field propagation model and a guide vector, delay summation beam forming is executed to obtain sound source preliminary distribution, then the distribution is regarded as a convolution result, a maximum likelihood model is introduced, and a two-stage deconvolution strategy of coarse estimation and Newton method fine optimization is adopted to obtain a high-resolution sound source. According to the multi-sound-source positioning method, subgrid-level analysis of sound source positions and amplitudes is achieved, finally, all frequency results are fused, continuous sound source images are smoothly output through a two-dimensional Gaussian kernel, the resolution and real-time performance of multi-sound-source positioning are remarkably improved, and the multi-sound-source positioning method is suitable for high-precision acoustic imaging in a complex sound field.

The invention discloses a formation decoupling sound source localization method and device based on deep learning and a readable medium, and the method comprises the steps: constructing and training a sound source localization model, and obtaining a trained sound source localization model; acquiring a first sound source signal received by a first microphone and a second sound source signal received by a second microphone in the microphone array; calculating generalized cross-correlation frequency domain representation between the first sound source signal and the second sound source signal based on the first sound source signal and the second sound source signal; obtaining a frequency domain feature based on the guide vector between the first microphone and the second microphone and the generalized cross-correlation frequency domain representation; determining an input feature based on the frequency domain feature, and inputting the input feature into a trained sound source localization model to obtain a candidate sound source angle and a confidence coefficient corresponding to the candidate sound source angle; and post-processing the candidate sound source angle to obtain a sound source positioning result. The invention solves the problems that the existing sound source localization method based on deep learning is large in calculated parameter quantity and cannot be applied to embedded equipment and the like.

The invention discloses a robot dog monitoring system for bird sound source positioning and tracking, and the system comprises a sound collection module which is used for collecting a multi-channel sound signal, and carrying out the preprocessing of the multi-channel sound signal; the edge calculation module is used for processing based on the preprocessed multi-channel sound signals to obtain a sound source positioning result; the robot dog motion control module is used for receiving the sound source positioning result, performing path planning in combination with a control algorithm, driving a robot dog to autonomously move to approach a sound source, and integrating a sound source array sensor to realize environment perception and navigation; the image recognition module is used for constructing a bird recognition model and deploying the bird recognition model in an image recognition sensor to obtain a bird recognition result; and the remote monitoring module is used for receiving and displaying the sound source positioning result, the motion trail of the robot dog and the bird recognition result in real time. According to the invention, an efficient and intelligent solution is provided for bird monitoring.

The invention belongs to the field of sound source localization, and particularly relates to an FPGA accelerated sound source localization algorithm implementation method and system. The method comprises the following steps: acquiring an audio signal through a microphone array with more than two channels to obtain a time domain digital signal corresponding to the audio signal; after the digital signal is converted into a frequency domain signal through the FPGA, the frequency domain signal is stored in a memory outside the FPGA in parallel through a parallel interface of a protocol with parallel transmission capability; the capacity of the memory is greater than that of storage resources in the FPGA chip; acquiring the stored frequency domain signal from the memory by using the protocol through the FPGA, calculating the cross-power spectral density of each microphone pair in the microphone array in parallel according to the frequency domain signal, and storing the calculated cross-power spectral density in the memory in parallel through a parallel interface of the protocol; through the FPGA, the cross-power spectral density is obtained from the memory, and in combination with the obtained pre-stored TDOA value, the response intensity of each microphone pair in the microphone array is calculated in parallel for realizing sound source localization.

The invention relates to the technical field of intelligent vehicle-mounted systems, and discloses a vehicle-mounted voice interaction method and system and a readable storage medium, and the method comprises the steps: synchronously collecting initial voice and video data in a vehicle-mounted environment; performing wake-up word detection through a local acoustic model, and based on the detection confidence, extracting a mouth shape visual feature sequence by using a mouth shape recognition model to perform mouth shape verification so as to obtain a wake-up state and sound source positioning information; activating an interaction module at a corresponding position, and performing semantic recognition on the collected interaction voice and video data through a local model and a cloud model respectively; and finally, carrying out fusion cross validation on the local semantic recognition result and the cloud semantic recognition result to generate a final semantic recognition instruction, and executing corresponding operation by the vehicle-mounted system. According to the method, the recognition accuracy, the response speed and the robustness of vehicle-mounted voice interaction in a complex environment are improved, the false wake-up rate is effectively reduced, and the user experience is optimized.

The invention discloses a cutting pick wear detection method and system for a heading machine, and relates to the technical field of mining machinery state monitoring, and the method comprises the steps: obtaining a cutting pick tool seat and a tool bit, fixing the tool bit on the tool seat through a plurality of rotating shafts, and arranging a plurality of high-bandwidth acoustic emission sensors on the rotating shafts; identifying a rotation detection signal by using a high-bandwidth acoustic emission sensor, and extracting characteristics such as acoustic emission pulse starting time and peak amplitude; constructing a sound source space positioning model to obtain a sound source positioning result; and mapping a sound source positioning result to the rotating shaft three-dimensional model to identify hidden wear, and outputting a risk level. The technical problems that the traditional detection means is difficult to accurately identify the hidden wear of the heading machine cutting tooth rotating shaft and cannot comprehensively and accurately acquire wear information to meet the accurate evaluation requirement are solved, and the accurate identification and risk grade evaluation of the hidden wear of the heading machine cutting tooth rotating shaft are achieved; and the accuracy and comprehensiveness of cutting pick wear detection are improved.

The invention discloses a sound source localization and distance measurement method, device and equipment based on a microphone array and a storage medium, and relates to the technical field of acoustics, and the method comprises the steps: collecting a frequency sweeping signal played by a sound source through the microphone array, obtaining the audio data of each channel, obtaining a cross-correlation sequence through generalized cross-correlation and phase transformation weighting processing, and obtaining a distance measurement result; constructing a current to-be-processed set, processing other sequences again by taking the first sequence as a reference to obtain a new sequence group, discarding the reference sequence, taking the new group as a to-be-processed set, repeating the iteration step until only one to-be-processed sequence is left in the set, and performing up-sampling on the sequences to obtain a to-be-processed set; extracting a first main peak position to obtain a time delay estimation value of a decimal sampling level so as to determine an incident angle of a sound source relative to an array normal, performing time delay alignment on each cross-correlation sequence, constructing a single-channel beam forming signal based on an alignment result, and determining a second main peak position so as to determine a sound source distance, the efficiency of sound source localization and distance measurement is improved.

The invention provides a far-field sound source localization method applied to a transformer substation, and relates to the field of sound source localization, and the method comprises the steps: obtaining a target frequency sound in the transformer substation, and converting the target frequency sound into a spherical harmonic domain multi-channel observation vector; inputting the spherical harmonic domain multichannel observation vector into a preset network model to obtain a spherical harmonic domain mask matrix, and obtaining an in-band smooth covariance based on the spherical harmonic domain mask matrix; the preset network model is used for filtering the spherical harmonic domain multi-channel observation vector; according to the in-band smooth covariance, a spatial spectrum matrix is obtained, and the spatial spectrum matrix comprises spatial spectrum values in different candidate sound source directions; performing multi-sound source distinguishing on the spatial spectrum matrix to obtain a multi-source direction set, and realizing far-field sound source positioning of the transformer substation; the multi-source direction set comprises polar angle and azimuth angle coordinates of each target sound source direction and is used for reflecting the sound source direction in the transformer substation. The method solves the problems that the noise interference of the transformer substation is large and multiple sound sources are difficult to distinguish, and realizes the accurate positioning of the sound sources in the transformer substation.

We provide a digital twin system for detecting and locating natural gas leaks in utility tunnels based on sound source localization. [Solution] In this system, a methane sensor is placed in the natural gas chamber of a common utility seismic tunnel, and when it detects that the methane concentration has reached a preset threshold, it sends an alarm signal to a mobile unit. The mobile unit autonomously moves to the natural gas leak area in the natural gas chamber based on the alarm signal and collects natural gas leak acoustic signals. The signal collection and location unit performs leak location for the natural gas leak source using a leak acoustic difference algorithm and feeds back the location of the located natural gas leak source to the mobile unit. The mobile unit autonomously moves to the location of the natural gas leak source and transmits the location of the leak source to a data aggregation unit on the common utility seismic tunnel server. The twin system updates the location results in a digital twin model in real time and virtually visualizes the common utility seismic tunnel.

The invention relates to the technical field of teaching evaluation, in particular to a preschool education practical teaching evaluation device and method, and the method comprises the steps: collecting a classroom thermodynamic diagram and sound source data through the synchronous starting of an infrared camera and a microphone array, carrying out the non-uniformity correction of the thermodynamic diagram, carrying out the noise reduction of the sound source data, and eliminating the environment interference; performing threshold segmentation on the thermodynamic diagram to generate a binary focus area, calculating geometric features of the area, and filtering sound source positioning data to generate a teacher movement track; pre-storing an ideal overlap ratio growth curve of each teaching stage, and dynamically adjusting a scoring weight coefficient according to the deviation amplitude of the real-time change rate and the ideal curve; and displaying a three-dimensional superposition view of the thermodynamic diagram, the teacher track and the coincidence degree change curve in real time, and generating a teaching efficiency scoring report. A thermodynamic diagram is generated in real time through the infrared thermal imaging camera, the sight focus of an infant is quantified through temperature distribution, and high-precision positioning of a voice source of a teacher is achieved through the microphone array.

The invention discloses a construction and recognition method for a sound source recognition network of vehicles in a highway tunnel, and the method comprises the steps: setting a distributed microphone array in the tunnel, and collecting a vehicle audio signal; a MobileNetV3 model based on the Mel frequency spectrum is constructed; the Mel spectrum feature extraction module is used for taking the Mel spectrum feature extracted by the Mel spectrum feature extraction module as input, taking a vehicle audio signal type as output, and training a MobileNetV3 model based on the Mel spectrum to obtain a sound recognition model; constructing a sound source localization model; according to the method, the MobileNetV3 model based on the Mel frequency spectrum is adopted for sound recognition, the sound source positioning model is constructed in a combined mode for sound source positioning, the MobileNetV3 model and the sound source positioning model work cooperatively, the feature description capability of abnormal sound of a vehicle is enhanced, the influence of tunnel echo and environment noise on recognition is effectively reduced, accidents in the tunnel are found in time and positioned accurately, and the method is suitable for popularization and application. The recognition and positioning accuracy of the vehicle sound source in the complex tunnel environment is improved, and the technical problem that in the prior art, the recognition precision of the accident sound in the tunnel is not high is solved.

The invention provides a positioning method and a positioning device, the positioning device can comprise a transducer module, the transducer module can comprise a plurality of transducers sharing the same piezoelectric material, and the plurality of transducers can be used for receiving sound signals emitted by a sound source. The positioning device can determine the position of the sound source according to the sound signals received by the plurality of transducers. The effective working area of the transducers sharing the same piezoelectric material is larger, and the transducers can receive sound signals with lower frequency due to the larger effective working area. In the process of positioning the sound source, the positioning device can sample the sound signal with the lower frequency by adopting the lower sampling frequency, so that the amount of data needing to be processed in unit time is less, and the power consumption is lower. The transducer module can be suitable for a positioning device with a limited accommodating space, and the accuracy of sound source positioning by using the transducer module is higher.

The embodiment of the invention provides a semantic map processing method and device for cleaning equipment, electronic equipment and a storage medium, and relates to the technical field of smart home equipment, and the method comprises the steps: obtaining target data corresponding to a voice annotation instruction, the target data at least comprising coordinate information, equipment parameters and a first timestamp, then, key semantics corresponding to the voice annotation instruction can serve as semantic tags, sound source localization compensation is conducted on the first timestamp according to the coordinate information and the equipment parameters, a second timestamp is obtained, then a map is updated based on the coordinate information, the second timestamp and the semantic tags, and a first semantic map corresponding to the cleaning equipment is obtained; therefore, the cleaning equipment can quickly realize map labeling based on the voice instruction, the operation threshold of a user is reduced, meanwhile, in the labeling process, through sound source positioning compensation, alignment of the voice instruction in time and space is ensured, and the accuracy of a voice standard is improved.

The invention discloses a sound source positioning identification system for electric power intelligent service and an operation method, and the system comprises an input module which is used for receiving an interaction demand of a user, and uploading the interaction demand of the user to an identification module; the identification module receives a user interaction demand, identifies and positions a user sound position based on the user interaction demand, and uploads an identification and positioning result to the processing module; one end of the processing module is connected to the recognition module, the other end of the processing module is connected to the output module, the processing module analyzes and processes the user question according to the received recognition and positioning result, and the output module answers the user question based on the analysis and processing result. According to the method, after the noise doped in the utterance spoken by the user is removed, the timbre, the speech speed, the audio frequency and the like in the statement of the user are recorded, and meanwhile, the user is captured, so that the virtual digital human can more accurately recognize and locate the user through a sound source, the interaction error is reduced, and the naturalness during interaction is improved.

The utility model relates to the technical field of pickup equipment, in particular to an intelligent acoustic positioning imager. The sound source positioning device comprises a lower shell, a sealing rubber mat and a microphone main board, the lower shell, the sealing rubber mat and the microphone main board are sequentially connected from outside to inside to form a sound source positioning assembly, and a plurality of digital silicon microphone structures are distributed on the sound source positioning assembly in an array mode. Each digital silicon microphone structure comprises a lower shell pickup port arranged on the lower shell, a rubber mat opening arranged on the sealing rubber mat and a mainboard pickup port arranged on the microphone mainboard, the microphone, the lower shell pickup port, the rubber mat opening and the mainboard pickup port are sequentially butted and communicated, the microphone is positioned on the microphone mainboard and is aligned with the mainboard pickup port, and the lower shell pickup port is positioned on the lower shell and is aligned with the mainboard pickup port. The digital silicon microphone structures are mutually independent. Multiple paths of high-sensitivity digital silicon microphones are arranged in an array mode to form a recording system for cooperative work, and the functions of sound source positioning, noise suppression and the like are achieved. And a stepped pickup channel is adopted, so that the direction and the distance to a sound source can be accurately positioned.

The invention provides a sound source localization method using time delay and dead reckoning. The method comprises the following steps: acquiring an original sound signal and carrying out noise reduction preprocessing; virtual sound rotation processing is carried out on the two sound source directions, interpolation simulation rotation is carried out on effective sound signals after noise reduction, and angle differences before and after rotation are compared to eliminate false angles; and finally calculating the position of the sound source through a geometric positioning algorithm by combining the unique sound source direction, the movement distance and the movement direction of the equipment and the time difference between the sound source and the two microphones. According to the method, acoustic orientation and a smart phone inertial navigation technology are deeply fused, a displacement vector is obtained by utilizing dead reckoning, and multi-position TDOA measurement information is combined, so that sound source three-dimensional space positioning only depending on single mobile equipment is realized, and the inherent defect that a traditional pure acoustic positioning method cannot measure distance is overcome.

The invention discloses a microphone array layout optimization method based on IGSA, and belongs to the field of sound source localization. The method comprises the following steps: firstly, constructing a topological structure of a microphone array as a rectangular array; then, the directivity and the directional diagram of the microphone array are adopted to express the performance of the microphone array; constructing a fitness function through the width of a main lobe, the level of a side lobe and the number of microphones; then, on the basis of a genetic algorithm, improving crossover and mutation steps, adopting a hierarchical crossover strategy and a similarity regulation and control mutation strategy, and simultaneously optimizing an array structure by a simulated annealing operator in an interspersed manner; and finally, outputting the optimal microphone array arrangement to meet the requirements of low sidelobe performance and high resolution. The IGSA algorithm is adopted to optimize the microphone array layout, so that more accurate global optimization, faster convergence speed and better multi-target balance are realized, and particularly, the number of microphones and the hardware cost are remarkably reduced while the sound source localization performance is ensured.

The invention relates to the field of audio data analysis, in particular to an audio data processing method and device, equipment and a storage medium. The method comprises the following steps: carrying out multi-angle audio continuous acquisition and scene noise suppression on a conference room through a surrounding microphone array, and generating a filtering optimization audio signal; performing three-dimensional time difference positioning calculation according to the filtered and optimized audio signal to obtain accurate sound source positioning information; personalized voiceprint analysis is carried out on the filtered and optimized audio signals, audio distribution modeling is carried out based on accurate sound source positioning information, and a multi-person conference audio field is constructed; performing parallel audio stream separation according to the multi-person conference audio field to generate an intelligent spliced audio segment; and performing deep semantic analysis and semantic logic correction on the intelligent spliced audio segment to generate an audio analysis result. According to the invention, rapid and accurate speaker audio recognition of a multi-person parallel conference is improved.

The invention discloses a digital human eye follow-up method based on sound source localization, belongs to the technical field of digital human and computer programs, and aims at obtaining the position of sound capable of attracting attention in a dialogue party or an environment by introducing a microphone array and a sound source localization algorithm, and driving a digital human to make corresponding response. The method has the advantages that the target sound source orientation is deduced by means of the microphone array, so that the sight following of the digital person to the dialogue party is realized, and the dialogue party and the user can feel more real experience in the interaction process. By means of the microphone array, gaze switching between a plurality of dialogue parties can be performed by voice.

The invention discloses an intelligent pickup and speech recognition system based on multi-modal fusion, and relates to the technical field of artificial intelligence and speech recognition crossing. The system comprises a main control module, a plurality of syllable points and a multi-modal fusion engine, wherein the multi-modal fusion engine comprises four core components, namely a sound source localization and separation component, an environment adaptive noise reduction component, a cross-modal feature fusion component and a dynamic context understanding component. Multi-modal data are acquired through an array microphone and an auxiliary sensor group, and the system realizes sound source localization and separation, dynamic environment noise suppression, multi-modal feature deep fusion and context semantic correction. According to the method, the robustness, the accuracy and the intelligent interaction capability of voice recognition are effectively improved, the voice interaction experience is improved in complex scenes such as a noise environment and accent change, and a more reliable voice processing solution is provided for intelligent voice interaction equipment.

The invention relates to the technical field of information acquisition, in particular to a fire-fighting emergency broadcast data information acquisition system which comprises the following steps: performing sound source positioning analysis on original data to obtain sound source distribution data; performing sound propagation loss estimation according to the sound source movement track data to obtain sound propagation loss data; emergency broadcast coverage demand period reference simulation evaluation is carried out according to the sound propagation loss data to obtain period reference data; and according to a strategy gradient algorithm, an emergency broadcast putting strategy adjustment model is constructed through the environment correction data, and the emergency broadcast putting strategy adjustment model is sent to a fire-fighting command cloud platform so as to execute fire-fighting emergency broadcast data information acquisition and analysis. According to the method, the attenuation degree of the broadcast signals under different environment conditions can be analyzed through estimation of the sound propagation loss, data support can be provided for the actual broadcast propagation effect, the broadcast signals can be optimally delivered according to the environment conditions, and therefore effective transmission of the signals is ensured.