15results about How to "Improve voice quality" patented technology

The invention discloses a Tibetan language Andole speech enhancement method suitable for specific noise and general noise, and relates to the technical field of low-resource language speech processing. The method specifically comprises the following steps: acquiring noisy voice information; preprocessing the noisy voice information, and dividing the processed data into a training set and a test set; a noise spectrum feature input by the noise classification module is optimized based on a weighted average method of a logarithmic power spectrum domain hard threshold; constructing a noise classification task and noise suppression task fused multi-target Tibetan speech enhancement model; training and testing the built speech enhancement model by using the training set and the test set to obtain a trained speech enhancement model; and inputting the actually collected noisy speech into the trained speech enhancement model to obtain an enhanced logarithmic power spectrum. Through effective fusion of the noise classification task and the suppression task, the quality and the intelligibility of the Tibetan language Andor dialect enhancement voice are improved, the human-computer interaction of the Tibetan language Andor dialect is more perfect, and the method has a positive effect on popularization of Tibetan language informatization.

This application provides a device control method, a recognition model training method, and related devices. The device control method includes: acquiring speech to be processed emitted by a target user; inputting the speech to be processed into a recognition model to obtain recognition information output by the recognition model, wherein the recognition information includes control speech and a target speech channel, or the recognition information includes control speech, a target speech channel, and a time-frequency masking code, wherein the target speech channel is a speech transmission channel with a signal-to-noise ratio greater than a signal-to-noise ratio threshold, and the time-frequency masking code is used for sound source localization of the target user; and waking up or controlling the device's functions based on the recognition information. This application improves the accuracy of recognizing control information in speech.

The invention discloses a speech noise reduction system in a multi-noise environment, and specifically relates to the technical field of speech noise reduction, comprising a basic division module that divides speech data into a plurality of basic speech segments of the same duration; a rationality analysis module that determines whether the segmentation points of adjacent segments are reasonable, and if not, an optimization marking module that finds new segmentation points for optimization; a loop module that repeatedly verifies the optimization result until all speech segments are segmented reasonably; a noise reduction module that extracts speech and noise features, and uses a noise reduction strategy to select a model for noise reduction processing; a reorganization module that reorganizes the noise-reduced speech segments into complete speech outputs; the invention divides a speech signal into a plurality of segments, and can match the most suitable noise reduction algorithm for each segment according to its noise features, and can cope with a more complex and unstable noise environment through a dynamically adapted noise reduction strategy, and ensure that the speech quality is well improved in various scenarios.

The invention discloses a speech enhancement method and a related device, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the enhancement of target speech data based on a speech enhancement model, and obtaining enhanced speech data, the speech enhancement model is constructed based on a U-shaped network added with a joint attention mechanism module composed of a self-attention module and a global space attention module, and on the basis of the feature modeling capability of the U-shaped network, on one hand, the self-attention module pays attention to the correlation of context information; and on the other hand, global features are fully modeled through a global space attention module, and intra-class compactness is improved, so that feature representation is optimized, the speech enhancement effect of the speech enhancement model is improved, and the speech quality of a speech enhancement result is improved.

The application discloses a microphone array sound pickup method, electronic equipment and computer readable storage medium. The sound pickup method comprises the following steps: fixed beam forming is performed on a voice signal received by a microphone array, and a beam forming direction of the microphone array is pointed to an estimated expected direction of arrival; blocking processing is performed on the processed voice signal, so that the voice signal from the expected direction of arrival is blocked, and only the voice signal from a non-expected direction of arrival is reserved; the processed signal is used as a reference signal, a first filter is used to filter out the signal from the non-expected direction of arrival and reserve the signal from the expected direction of arrival; and an update factor of the first filter is calculated according to the following formula (I), wherein the update factor of the first filter of the mth microphone channel is SNR f,d (ω, l) is Y f,d (ω, l) is a signal-to-noise ratio of Y f,d (ω, l) is a delay signal obtained by delaying the signal processed in the step S1, SNR m (ω, l) is a signal U m (ω, l) is a signal-to-noise ratio of Y. The application further improves voice quality.

The invention provides a speech enhancement method, a speech enhancement device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining original voice data; inputting the original voice data into a voice enhancement model, and encoding the original voice data through an encoder to obtain encoded voice features; performing first speech enhancement on the coded speech feature through a first speech enhancement module to obtain a first enhanced speech feature; performing second speech enhancement on the first enhanced speech feature through a second speech enhancement module to obtain a second enhanced speech feature; performing feature fusion on the first enhanced speech feature, the second enhanced speech feature and the coded speech feature through a feature fusion module to obtain a target enhanced speech feature; and decoding the target enhanced voice features through a decoder to obtain enhanced voice data. The voice quality of the voice can be improved and enhanced. The method and the device can be used for scenes such as e-commerce and online transaction.

The application provides a speech noise reduction method and device, the method comprises the following steps: obtaining air conduction sound signals and bone conduction sound signals, and bone conduction target event signal segments, bone conduction non-target event signal segments, air conduction target event signal segments and air conduction non-target event signal segments; fusing signals in at least part of frequency bands in the bone conduction target event signal segments and the air conduction target event signal segments to generate a fused signal; and performing noise reduction processing on the fused signal and the non-target event signal segments and then outputting. Thus, the bone conduction sound signals and the air conduction sound signals are effectively fused, so that the speech signal is reduced in noise, and the speech quality of the electronic device is improved.

The present application discloses a cross-language speech synthesis method, device, electronic device and storage medium, the method comprising: obtaining speech data of a target object and speech data of an object to be synthesized; wherein the speech data of the target object is in a first language; the speech data of the object to be synthesized is in a second language; the second language and the first language are different languages; obtaining a timbre feature matrix of the target object; and encoding the phonemes, pitches and phoneme durations of the speech data of the object to be synthesized, and adding a set note at the phonemes with the same pronunciation or fuzzy pronunciation to obtain processed encoded data; decoding the timbre feature matrix and the encoded data to obtain synthesized speech data based on the second language with the timbre feature matrix. The present application can make the synthesized speech data have the timbre of the target object while retaining the pronunciation habits of the second language, so as to improve the transferability of the language, and then improve the cross-language speech synthesis effect.

The invention provides a speech synthesis method and device, electronic equipment and a storage medium. The speech synthesis method comprises the following steps: acquiring an intermediate acoustic feature generated according to a target text, wherein the intermediate acoustic feature corresponds to a to-be-synthesized target speech; obtaining a prior noise signal, and extracting a time domain envelope feature of the target voice from the intermediate acoustic feature; and inputting the prior noise signal, the intermediate acoustic feature and the time domain envelope feature into a pre-trained neural vocoder, and obtaining a target voice which is output by the neural vocoder and is matched with the target text.

The invention relates to the technical field of artificial intelligence, and discloses a voice denoising real-time interaction method based on a cleaning robot, and the method comprises the steps: collecting a voice signal in a target environment through a preset cleaning robot; extracting a signal feature of the voice signal; performing noise suppression processing on noise in the voice signal according to the signal feature to obtain a primary de-noised signal of the voice signal; performing dynamic weighting on the primary de-noised signal by using a preset signal weighting algorithm and the signal features to obtain a weighted signal of the primary de-noised signal; generating an operation instruction of the cleaning robot according to the weighted signal; and generating a task sequence table of the cleaning robot according to the operation instruction, wherein the cleaning robot works according to the task sequence table. According to the invention, the efficiency of voice denoising real-time interaction based on the cleaning robot can be improved.

The invention relates to a voice signal processing method and device, electronic equipment and a storage medium. The method comprises the steps that content coding features, rhythm coding features and timbre coding features are acquired, the content coding features are used for representing the content of a voice signal, the rhythm coding features are used for representing the rhythm of the voice signal, and the timbre coding features are used for representing the timbre of the voice signal; content context construction is carried out on the content coding features based on the tone coding features and the rhythm coding features, and content context features are obtained; and performing voice reconstruction according to the timbre coding feature, the rhythm coding feature and the content context feature to obtain a target reconstructed voice signal. According to the technical scheme provided by the invention, high-quality speech reconstruction can be provided at a low code rate.

This disclosure provides a causal adaptive single-channel speech denoising method and apparatus. The method includes: acquiring noise information in a first time period and noisy speech information in a second time period; processing the noise information and noisy speech information to obtain a noise correlation matrix and a speech correlation matrix; performing generalized eigenvalue decomposition on the noise correlation matrix and the speech correlation matrix to obtain multiple initial feature vectors; generating a target filter vector based on the multiple initial feature vectors and the filter function of the initial filter; and generating enhanced target output speech information based on the target filter vector and the noisy speech information.

The audio signal processing method and system for suppressing echo provided in this specification controls the selection of the target audio processing mode according to the speaker signal strength. The method and system generate a corresponding control signal according to the speaker signal strength, and control the target audio processing mode according to the control signal, and perform signal processing on the microphone signal to obtain better voice quality. When the speaker signal does not exceed the threshold, the system selects the first mode, and performs signal processing on the first audio signal and the second audio signal to obtain the first target audio. When the speaker signal exceeds the threshold, the system selects the second mode, and performs signal processing on the second audio signal to obtain the second target audio. The method and system can switch the target audio processing mode according to the speaker signal, ensuring better voice quality in different scenarios and improving the quality of voice communication.

The invention relates to the technical field of noise suppression, in particular to a residual noise suppression method based on characteristic component filtering. A residual noise suppression method based on feature component filtering is characterized in that noise is suppressed by increasing correlation of voice frames, and adjacent small feature components are replaced with large feature components or the adjacent small feature components are removed. In most cases, the three methods provided by the invention all have a relatively high SegSNR score, which reflects the strong ability of noise reduction under the condition of a low signal-to-noise ratio; in the aspect of segmentation signal-to-noise ratio scoring, the three methods provided by the invention are obviously improved, and the PESQ score of auditory speech quality is almost the highest.

The application discloses a kind of regulation voice data effective information enhancement method and system, and steps successively include: regulation voice signal separation, regulation voice signal noise reduction and regulation voice signal enhancement;Regulation voice signal separation utilizes the characteristics of different regulation voice center frequency difference, phase difference etc., and the regulation voice of multiple interweaves is separated into effective single voice signal;Regulation voice signal noise reduction extracts pure regulation voice signal, and filters out background noise and the process noise brought by deinterleaving;Regulation voice signal enhancement carries out lossless enhancement to the phase-frequency characteristics of voice signal;The application in the complex air traffic control environment that multiple people speak simultaneously, there is weak effective signal or background noise interference, maintains stable high recognition rate, reduces error and improves the overall efficiency of system.