18 results about "Sound source separation" patented technology

The application provides a recording processing method and related devices. The method can include: an electronic device can perform sound source positioning based on the sound collected by a microphone, obtain the position of a target sound source and the number of sound sources in the recording environment, and then perform sound source separation on the sound collected by the microphone according to the position of the target sound source and the number of sound sources in the recording environment to obtain the sound corresponding to the target sound source, i.e., a target audio signal. The electronic device can also determine the signal-to-noise ratio and display the current sound pickup quality to the user. This method can monitor and display the sound pickup quality to the user in real time, so that the user can adjust in time when the sound pickup quality is poor, thereby obtaining high-quality audio and improving the user experience.

This invention provides a method, medium, and system for acoustic early warning of thermal runaway in lithium-ion batteries based on feature reconstruction, belonging to the field of lithium-ion battery technology. The invention constructs a positive sample set by collecting safety valve opening sounds through multi-condition thermal runaway experiments, and expands the samples using data augmentation. Multi-resolution Mel spectra are extracted from the audio signals. These Mel spectra are then input into a complex-domain phase-aware separation model for joint estimation of complex-domain amplitude masking and phase residuals. Physical prior corrections are applied to the reconstruction results using a sound source separation algorithm based on wave equation time-frequency inverse scattering and a low-rank sparse time-frequency matrix decomposition algorithm based on random matrix theory. The three corrected signals are weighted and fused to obtain a corrected Mel spectra, which are finally input into a temporal convolutional network to classify and identify the safety valve opening sounds and output a thermal runaway early warning signal. This invention solves the technical problem of insufficient accuracy in thermal runaway early warning caused by acoustic feature reconstruction distortion in complex noise environments.

The application discloses an audio processing method, device and equipment and a storage medium, relates to the technical field of audio processing, and discloses an audio processing method, which comprises the following steps: inputting a stereo audio signal into a preset sound source separation model to obtain a plurality of independent audio objects; obtaining original spatial information of each audio object from the stereo audio signal, and obtaining music structure information of the stereo audio signal; generating target spatial parameters of the audio objects in a three-dimensional immersive sound field based on the original spatial information and the music structure information, wherein the target spatial parameters comprise position coordinates and / or movement trajectories; and rendering each audio object based on the target spatial parameters to obtain a multi-channel immersive audio signal. The application can improve the generation quality of the multi-channel immersive audio signal.

A sound source separation device according to an embodiment of the present disclosure includes a plurality of microphones, a matrix unit, and an output unit. The plurality of microphones may receive a plurality of microphone input signals transmitted from a plurality of sound sources. The matrix unit generates an objective function according to an estimated source vector and an estimated noise vector estimated based on the plurality of microphone input signals, and replace a first term and a second term included in the objective function using a log-likelihood function to estimate a demixing matrix. The output unit provides output vectors calculated based on the microphone input signals and the demixing matrix.

The embodiment of the invention discloses a method, device and equipment for training a sound source separation model. In the embodiments of the present invention, a plurality of sound signals of a wearer and / or a non-wearer are obtained, the plurality of sound signals are generated by recording a playing signal by an intelligent device in different scenes and different paths, and the playing signal is a sound signal emitted by the wearer and / or the non-wearer; determining a plurality of room impulse response (RIR) functions according to the plurality of sound signals; generating a plurality of basic training data according to the plurality of RIR functions; training a basic separation model according to the multiple basic training data; acquiring a plurality of real scene data of a wearer and a non-wearer; and performing fine tuning on the basic separation model according to the multiple pieces of real scene data to generate a target separation model. Through the method, the target separation model is generated, the voice signal separation effect is effectively improved, and the user experience is improved.

This invention relates to the field of audio signal processing technology, and discloses a method and system for dynamic audio control optimization based on convolutional neural networks. The method includes: separating the mixed audio signals using a source separation convolutional neural network to obtain independent estimated spectra for each source category; extracting energy demand prediction vectors and transient feature descriptors for each source category using a spectral residual convolutional neural network; calculating the driving characteristic matching score between each source category and each speaker unit; performing propagation calculations based on the room transfer function and constructing an arrival power prediction matrix; calculating the masking threshold matrix and perceived loudness estimate for each listener position; solving for the optimal power allocation coefficient through a joint optimization objective function; extracting position-specific perception sensitivity coefficients using an auditory masking perception convolutional neural network; generating adaptive dynamic compression gain values ​​and finally outputting the driving signals for each speaker unit.

The present disclosure provides a sound source separation method and device, and relates to the technical field of intelligent vehicles, which comprises the following steps: performing sound source separation on a plurality of sound collection signals in a previous observation window according to a separation matrix corresponding to a previous round of sound source separation to obtain a plurality of separation estimation signals corresponding to the previous round of sound source separation, and obtaining a speech existence probability corresponding to the separation estimation signals; updating the separation matrix corresponding to the previous round of sound source separation according to the speech existence probability; and performing sound source separation on a plurality of sound collection signals in a current observation window according to the updated separation matrix to obtain a plurality of separation estimation signals corresponding to the current round of sound source separation. The speech existence probability of the separation estimation signals obtained based on the previous round of sound source separation is used to update the separation matrix, so that the speech existence information of the sound collection signals in the previous observation window is added when the separation matrix is updated, and the separation coefficients of various sound sources are adjusted accordingly, thereby enhancing the separation effect of the sound sources.

The objective is to provide an information processing device and program that can efficiently generate time-saving content. [Solution] The information processing device of this embodiment is an information processing device that receives and processes content data, and comprises: an acquisition unit that stores audio data acquired from the content data in a storage area; an inference unit that performs sound source separation processing using the audio data stored in the storage area and outputs sound source data; and a generation unit that generates time-saving content with a shortened playback time of the content data based on the output sound source data.

The application relates to the technical field of medical informatics, and particularly relates to an AI voice recognition-based psychiatric electronic medical record generation device. A voice processing module collects doctor-patient conversation audio signals, generates a time-stamped text sequence through sound source separation and voice recognition. A semantic analysis module performs context modeling, entity recognition and relationship extraction on the text sequence, and outputs clinical entities and semantic relationships. A knowledge graph module performs graph reasoning based on psychiatric clinical knowledge data, and generates a diagnosis hypothesis. A template adaptation module selects a medical record template and fills in fields according to the analysis result and the diagnosis hypothesis, and generates a preliminary medical record document. A quality control module performs multistage checking on the document, and feeds back the checking result to each module to realize parameter optimization. Through data flow conversion and closed-loop feedback mechanism among the modules, the device realizes automatic conversion of unstructured doctor-patient conversation into standardized medical records, and effectively improves the accuracy and integrity of psychiatric medical record recording.

This application relates to a method, system, device, and medium for separating overlapping speech in video conferencing based on AI noise suppression, belonging to the field of online video conferencing service technology. The method for separating overlapping speech in video conferencing includes: acquiring and cleaning the mixed audio stream of participants, segmenting and converting it into a short-time frame spectrogram; extracting the voiceprint features from the short-time frame spectrogram to obtain a general acoustic feature vector and a participant representation vector; separating and mapping the general acoustic feature vector according to a preset sound source separation network to generate a sound source speech mask and record potential sound source labels; aggregating the participant representation vector and the sound source speech mask according to the potential sound source labels to obtain a participant speech mask; reconstructing the short-time frame spectrogram based on the participant speech mask, and adaptively applying gain and noise suppression to obtain the participant speech stream; using a deep learning model to distinguish speech, noise, and multiple sound sources, achieving the separation of overlapping speech and improving speech intelligibility in noisy environments.

The system determines the sound source separation model best suited to the user's environment. [Solution] The sound source separation model determination device acquires voice data of one user speaking in a predetermined usage environment, mixes the voice data with at least one clean voice data, separates the mixed voice using each of a plurality of sound source separation models, and determines and outputs a sound source separation model to be used for sound source separation of voice data acquired in the predetermined usage environment based on the speech recognition result of the separated data corresponding to the clean voice data among the plurality of separated data.

The present application provides an information processing apparatus and a program capable of effectively generating time-shortened content. The information processing apparatus receives content data and processes the content data. The information processing apparatus comprises: an acquisition part, which stores sound data acquired from the content data into a storage area; an inference part, which performs sound source separation processing by using the sound data stored in the storage area, and outputs sound source data; and a generation part, which generates, on the basis of the outputted sound source data, time-shortened content in which the playback time of the content data is shortened.

Disclosed is a voice processing apparatus for processing voices of a plurality of speakers. The voice processing apparatus comprises: a microphone configured to generate voice signals in response to the voices of the plurality of speakers; a communication circuit configured to transmit and receive data; memory; and a processor, wherein the processor, on the basis of instructions stored in the memory, performs sound source separation of the voice signals on the basis of sound source positions of each of the voices, generates separate voice signals associated with each of the voices according to the sound source separation, determines output modes corresponding to the sound source positions of each of the voices, and uses the communication circuit to output the separate voice signals according to the determined output modes.

The application relates to the field of acoustic signal separation, in particular to an improved DPRNN sound source separation method, which comprises the following steps: acquiring an original mixed signal; constructing an improved DPRNN acoustic signal separation model, wherein the model comprises an encoder, a separation layer and a decoder; processing the original mixed signal by using the encoder to obtain coding features; performing signal separation by using the separation layer according to the coding features, so as to extract independent source signal features from the mixed signal; and finally, restoring the source signal features by using the decoder to output separated acoustic signals. The application realizes the separation of complex acoustic signals, can be well applied to a speech separation task, can provide clear signal data for a fault diagnosis task, and enhances diagnosis accuracy.

This invention discloses an automated customer service and emotion response method integrated into a companion terminal, specifically relating to the field of speech signal processing technology. It addresses the problem that existing sound source separation technologies in multi-person environments damage the emotional acoustic features of speech, leading to inaccurate emotion recognition. The method first predicts the potential damage to emotional features during separation, initiates separation when the risk of damage is high, and analyzes the non-physiological instability patterns of the emotional feature time trajectory in the separation results. Based on these patterns, a sound source separation strategy aimed at restoring trajectory continuity is generated. This strategy is then used to reprocess the mixed speech, obtaining speech with enhanced emotional features, and performing emotion recognition and response to achieve a more accurate understanding and empathetic response to user emotions.

This application relates to the field of vehicle control, specifically to a vehicle sound transmission method, a vehicle, a vehicle controller, and a storage medium. The vehicle includes a microphone located outside the vehicle and a speaker located inside the vehicle. The vehicle sound transmission method includes: acquiring the occupant's sound transmission request, which indicates the target external sound source the occupant expects the vehicle to transmit; acquiring mixed external sound; separating the target sound signal from the mixed external sound based on a sound source separation model and the sound transmission request, the target sound signal being the sound signal emitted by the target external sound source; and playing the target sound signal inside the vehicle. This application can shield irrelevant external noise and enable occupants to perceive key safety sounds from outside the vehicle, improving driving safety.