71 results about "Quality voice" patented technology

The invention relates to a multi-microphone array beam forming signal enhancement method and device, and the method comprises the steps: obtaining a multi-channel time domain signal collected by a multi-microphone array, and carrying out the time-frequency conversion, and obtaining a plurality of time-frequency domain signals; acquiring a spatial distribution vector of the multi-microphone array, and performing deformation compensation processing on the complex number of time-frequency domain signals to obtain sound field consistency signals; performing sound source direction feature extraction on the sound field consistency signal, and performing complex time-space attention beam forming network processing to obtain a beam forming signal; performing beam direction and gain parameter optimization on the beam forming signal through a preset adversarial environment simulator to obtain a dynamic frequency band enhanced signal; and performing inverse time-frequency conversion on the dynamic frequency band enhanced signal, and performing low-delay optimization to obtain a target quality voice output signal. According to the invention, signal deformation compensation can be carried out more accurately.

The invention discloses a lecturer video automatic generation method based on AI speech synthesis and animation driving. The method comprises the following steps: performing structured analysis on a PPT or a text script through an improved interior point method and an incremental shortest path algorithm; performing semantic grouping by applying a full-dynamic parallel single-link clustering algorithm and generating an enhanced script with an expressive mark; a CosyVoice technology is combined with a low-rank approximation method to generate a high-quality voice data stream; establishing a mapping relation between contents and action expressions through semantic analysis, and generating a complete action expression instruction set; and driving the digital human model by using the msueTalk technology, and generating a final lecturer teaching video through a parallel rendering algorithm. According to the invention, the method achieves the efficient and automatic generation of the education video, remarkably improves the content production efficiency, reduces the production cost, and guarantees the specialty and expressive force of the teaching video.

The embodiment of the invention discloses a voice instruction-based processing method, device and system. A specific embodiment of the method comprises the following steps: identifying voice data, and synchronously sending the voice data to a terminal and a cloud; in response to the received user intention information sent by the terminal or the cloud or the recognized user intention information, preset operation corresponding to the user intention information is executed, and the user intention information sent by the terminal is obtained by recognizing the received voice data by the terminal. The user intention information sent by the cloud is obtained by recognizing the received voice data by the cloud; and in response to the recognized user intention information, sending a cancelling signal to the terminal and the cloud, the cancelling signal being used for interrupting tasks corresponding to the voice data in the terminal and the cloud. According to the embodiment, through multi-terminal identification and cooperation, high-quality voice instruction processing is realized, and the user experience and the system practicability are improved.

The invention discloses an implementation method and device for cloud rendering of a voice interaction digital human, computer equipment and a readable storage medium, and the method comprises the steps: firstly constructing the voice interaction digital human, carrying out the audio lip movement synchronization and personification configuration, and then carrying out the real-time cloud rendering, and placing the voice interaction digital human in a front-end page. After front-end voice interaction input of a user is obtained, interaction feedback of a digital human is generated through previous configuration, and then the feedback is cloud-rendered to a front-end page in real time. According to the method, the requirements of various industries for high-quality voice interaction digital people are met, meanwhile, the requirements of user equipment are reduced by means of the cloud rendering technology, and the user experience is improved.

The invention relates to a service compliance dynamic evaluation system based on real-time voice recognition, and belongs to the cross technical field of artificial intelligence and service compliance management. The system comprises a voice signal enhancement acquisition unit, a voice analysis and risk initial judgment unit, a dynamic evaluation iteration unit and a compliance risk disposal unit. The voice signal enhancement acquisition unit processes low-quality voice and generates a voice data set; the voice analysis and risk initial judgment unit is used for transferring voice in real time, extracting a dialogue intention and identifying violation contents and interactive emotions; the dynamic evaluation iteration unit outputs compliance scores and violation details and is in butt joint with a manual labeling platform; and the compliance risk disposal unit generates a risk label, carries out linkage training and appeal review, and forms a compliance risk disposal scheme. According to the invention, full quality inspection of service scenes in multiple industries such as finance, operators and the like is realized, the voice transfer accuracy and compliance rectification rate are improved, the verbal skill violation complaint rate is reduced, and dynamic monitoring and closed-loop disposal of service compliance are achieved.

The invention discloses a millimeter wave voice signal processing method and system based on model and data hybrid driving, and relates to the field of wireless communication and signal processing. The method comprises the following steps: collecting and preprocessing a radar echo signal, and obtaining an original voice signal through phase demodulation; a model-driven virtual vector compensation algorithm is utilized to enhance an observation phase and amplify a phase change caused by voice vibration; after the signals are converted to a time-frequency domain, amplitude denoising and phase optimization are carried out in sequence by adopting a data-driven multi-stage denoising network, and finally, the high-quality voice signals are recovered through short-time inverse Fourier transform. Through the model and data hybrid driving technology, the definition and the anti-interference capability of millimeter wave voice signal processing are remarkably improved.

The embodiments of the present disclosure relate to a method and apparatus for providing voice content, a device, and a storage medium. The method provided herein comprises: in response to a voice request associated with a target page and on the basis of the target page, generating broadcast information, wherein the broadcast information comprises a plurality of text fragments, and each text fragment is associated with a corresponding virtual character (210); on the basis of the broadcast information, generating a plurality of voice fragments corresponding to the plurality of text fragments, wherein the timbre of each voice fragment is determined on the basis of a virtual character corresponding to the voice fragment (220); and on the basis of the plurality of voice fragments, providing voice content associated with the target page (230). In this way, the embodiments of the present disclosure can provide higher-quality voice broadcast content.

The invention relates to the technical field of speech translation data processing, and particularly discloses a speech translation method and device for solving speech ambiguity, and the method comprises the steps: obtaining speech data, analyzing the speech data, and adjusting translated speech feature data. According to the method, background noise in voice data can be effectively removed, environmental interference is reduced, voice definition and recognizability are improved, high-quality voice data support is provided for subsequent voice recognition and translation, translation voice feature data are preprocessed and adjusted, ambiguity in the voice data can be effectively recognized and eliminated, and the voice recognition and translation efficiency is improved. According to the method, the translation result is ensured to be more accurate, the translation efficiency is improved, finally, the speech ambiguity is fed back through the speech translation feedback device, ambiguity and errors in the translation process can be recognized and adjusted in time, and the speech translation accuracy is improved.

The invention discloses a voice noise reduction method and device for a multi-person scene, electronic equipment and a storage medium, and relates to the technical field of voice signal processing. The method comprises the following steps: acquiring an audio signal and a video image of a target space scene; determining audio perception information matched with the audio signal and a visual voice activity detection result corresponding to the video image; fusing the audio perception information and the visual voice activity detection result, and determining a target voice sounding object when the voice activity fusion result indicates that the voice activity exists; and positioning a human face corresponding to the target voice sounding object to obtain position change information, updating a pickup direction, controlling beam forming processing, and outputting a denoised target voice signal. According to the scheme provided by the invention, the voice of the current effective speaker can be accurately separated and enhanced from the aliasing audio signals, meanwhile, the interference of other speakers and environmental noise is inhibited, and help is provided for realizing high-quality voice interaction and recognition.

The invention discloses a controllable voice generation method and device based on multi-agent dynamic scheduling, and belongs to the technical field of voice synthesis, and the method comprises the steps: constructing a multi-agent voice generation frame comprising a central scheduling module, an identity agent, an emotion agent and an environment agent; a central scheduling module analyzes a user instruction and outputs a structured task plan to drive each agent to generate primary voice output of identity, emotion and environment dimensions, and a cooperation cost matrix between the agents is constructed according to the primary voice output; the optimal execution path of the multiple agents is solved through an optimization algorithm based on the cost matrix, the agents are executed in a cascading mode based on the optimal execution path, and finally sound mixing is completed and high-quality voice is output. According to the method, the naturalness, the semantic consistency and the overall quality of the synthesized voice in a complex scene can be remarkably improved, and the method is suitable for various man-machine interaction application scenes such as intelligent voice assistants, virtual digital humans, immersive entertainment, barrier-free voice services, personalized content creation and the like.

The invention provides an extremely low rate voice communication method and related equipment. The method comprises the following steps: extracting a first feature and a second feature from acquired voice information; the first feature reflects semantic information of the voice information; the second feature reflects the acoustic feature of the voice information; calculating an entropy value of variational posteriori distribution of the first feature, and adjusting the first feature according to the entropy value to obtain a third feature; performing semantic quantization on the third feature to obtain a first index; performing acoustic quantization on the second feature to obtain a second index; and gradually restoring details of the voice information based on the first index and the second index so as to complete transmission of the voice information. According to the embodiment of the invention, through semantic and acoustic feature fusion and entropy modulation and quantization, the compression efficiency is improved, the bit demand is reduced, and high-quality voice transmission and restoration are realized.

The invention provides a driving emotion early warning method and system based on voice analysis, relates to the technical field of voice emotion recognition, and effectively solves the interference problem of vehicle-mounted dynamic strong noise by deploying a microphone array and a noise sensor in a cockpit and combining multi-channel noise reduction algorithms such as beam forming and linear beam minimum variance. A high-quality voice instruction is extracted from a source; on the basis, the driving intention of the clear voice signal is accurately recognized by using the deep neural network, so that the accuracy is remarkably improved; more importantly, according to the method, the instability Ls and the high interactive friction probability Pf are recognized innovatively through calculation instructions, real-time quantitative evaluation on the man-machine interaction fluency is achieved, when the interactive friction probability Pf exceeds a preset threshold value, the system can automatically trigger self-adaptive strategy adjustment, and therefore the situation that a driver is distracted due to recognition errors is avoided, and user experience is improved. And the interaction experience and the driving safety are greatly enhanced.

The utility model discloses a sound processing system, comprising a pickup module used for picking up the sound of a user; the playback module is used for converting the electric signal into a sound signal and playing the sound signal; the information processing module is used for receiving and processing the signal of the pickup module and outputting the enhanced voice signal to the playback module; and the power management module is used for supplying power to the sound processing system and comprises a direct current-direct current charging management unit and an overvoltage and overcurrent protection device. By means of the mode, on the premise that normal oxygen uptake of a patient is guaranteed, barrier-free communication between the patient and the outside world is achieved, voice enhancement is achieved by combining noise elimination, echo suppression, howling suppression, gain control and the like, and high-quality voice transmission is achieved.

The invention discloses a dialect speech recognition method and system in a vehicle-mounted scene, and belongs to the technical field of speech recognition. Aiming at challenges such as noise, dialect diversity and speaker overlapping in a complex environment in a vehicle, a systematic solution from data acquisition and data preprocessing to model training and decoding is provided. In the data acquisition stage, diversified high-quality voice data are acquired by arranging a far-field microphone, wearing a near-field microphone and recording noise in a vehicle, and text and speaker timestamp labeling is carried out. According to the method, the performance of the voice recognition system in a complex vehicle-mounted scene is remarkably improved, and the method is suitable for practical application scenes such as vehicle-mounted navigation and voice assistants under the dialect condition.

The application discloses a voice data loss recovery processing method and device, equipment and a storage medium, and relates to the technical field of voice transmission. The method comprises the following steps: performing frame processing on received voice message data to obtain frame voice data; when signal loss is detected, performing voice reconstruction on the frame voice data based on compressed sensing to obtain initial voice recovery data; and performing dynamic voice filtering on the initial voice recovery data through a preset filtering network to obtain target voice recovery data. The voice message data is first subjected to frame processing, the voice is reconstructed based on compressed sensing by using the sparsity of the voice signal when the signal is lost, and then dynamic filtering is performed through the preset filtering network, so that high-quality voice data is finally output. The method solves the problems of bandwidth waste caused by redundant transmission and poor effect of traditional interpolation filtering in the prior art, realizes the effects of saving bandwidth, efficiently recovering lost voice frames and improving voice quality, and meets the demand for high-quality voice communication.

The embodiments of the present disclosure disclose a processing method, device and system based on voice instructions. A specific implementation of the method includes: recognizing voice data, and synchronously sending the above-mentioned voice data to the terminal and the cloud; in response to receiving the user intention information sent by the above-mentioned terminal or the above-mentioned cloud or identifying the user intention information, executing the preset operation corresponding to the above-mentioned user intention information, wherein the user intention information sent by the above-mentioned terminal is obtained by the above-mentioned terminal recognizing the received voice data, and the user intention information sent by the above-mentioned cloud is obtained by the above-mentioned cloud recognizing the received voice data; in response to recognizing the user intention information, sending a cancellation signal to the above-mentioned terminal and the above-mentioned cloud, wherein the above-mentioned cancellation signal is used to interrupt the task corresponding to the above-mentioned voice data in the above-mentioned terminal and the above-mentioned cloud. This implementation method achieves higher-quality voice instruction processing through multi-terminal recognition and collaboration, thereby improving user experience and system practicality.

The present application discloses a video call voice processing method, a communication terminal, and a readable storage medium. The video call voice processing method includes: identifying a target person in a current video image; obtaining an answering parameter of the target person, where the answering parameter is used to identify the sound intensity heard by the target person and includes at least one of the position of the target person in the current video image, the action of the target person, and the voice of the target person; adjusting the gain of a sound collection device according to the answering parameter, and transmitting a voice signal collected by the adjusted sound collection device to a target terminal. The present application can adjust the input gain of its own microphone according to the situation of the other party in a call scenario, thereby facilitating the provision of high-quality voice call services for users.

The invention discloses a voice cloning model training method and device, and a voice cloning method and device, and the method comprises the steps: constructing a text alignment module, a first pitch extraction module, a second pitch extraction module and a rhythm extraction module, and carrying out the training of the modules, obtaining a trained text alignment module, a trained first pitch extraction module, a trained second pitch extraction module and a trained rhythm extraction module; combining the first training data set with a voice style diffusion module, a decoder and a random duration prediction module to construct a voice clone model, and training the voice clone model by adopting the first training data set to obtain a trained voice clone model; and performing fine tuning on the trained voice clone model by adopting the second training data set to obtain a fine-tuned voice clone model, and cloning high-quality voice close to the target tone only by providing reference voice of which the duration is at least the preset duration.

The invention discloses a voice reconstruction method and device, a storage medium and a program product, and relates to the technical field of audio processing, and the method comprises the steps: obtaining to-be-reconstructed original voice data, and extracting the granularity voice frame features of the original voice data at each frame rate; calculating the voice information density of each granularity voice frame feature in each time window; screening granularity frame feature fragments according with a preset granularity proportion from each granularity voice frame feature according to the voice information density; the granularity proportion predefines the time proportion of the fragment duration of each granularity frame feature fragment in a unit time period; and performing voice reconstruction based on each granularity frame feature fragment to obtain corresponding reconstructed voice data. Therefore, through voice information density analysis, dynamic frame segment distribution of a variable frame rate is realized, high-sound-quality reconstruction is ensured, the coding complexity and delay are remarkably reduced, and the real-time performance and the self-adaptive capability of the whole system are improved.

The invention provides a voice cloning system and method, and the system comprises a data preprocessing module, a feature extraction module, a model training module, and a reasoning generation module, and the data preprocessing module is used for carrying out the human voice accompaniment separation, audio cutting, and automatic marking of an original audio; the feature extraction module is used for extracting a self-encoding feature and a Mel spectrum feature from the audio and pairing the self-encoding feature and the Mel spectrum feature with the text length; the model training module is used for performing fine tuning training on the basis of a small amount of reference audio data by combining a GPT-like model and a VITS and Valle model architecture; and the reasoning generation module is used for generating target audio according to the reference audio and the text provided by the user. According to the method and the device, high-quality voice cloning and text-to-voice conversion can be realized only by a small amount of data sets, so that the user experience is improved, and the development cost is also reduced.

The invention discloses a personalized voice cloning method and system based on deep learning, which relates to the technical field of voice cloning, including: collecting voice samples of target users; extracting high-dimensional features of voice samples based on convolutional neural networks; encoding high-dimensional features into low-dimensional vectors based on variational autoencoders; using a preset synthesis model to convert the low-dimensional vector into a voice feature sequence; using the text and voice feature sequence corresponding to the voice sample as training samples, training the preset synthesis model to obtain a trained synthesis model; extracting the voice feature sequence of the text to be cloned based on the trained synthesis model; inputting the voice feature sequence of the text to be cloned into a speech synthesis model based on an improved WaveNet structure to generate a target voice waveform. The invention can achieve high-quality voice cloning based on a small amount of voice data.

This application provides an earphone case, a wireless communication device, and a method for using the same. The earphone case includes a case body, a cover assembly, and a magnetic component. The cover assembly includes a lid, a microphone module, and a playback module. The lid can be closed and detached from the case body. The playback module is used to play sound. At least a portion of the lid is metal. The magnetic component is detachably mounted to the case body and can fix the lid when the cover assembly is separated from the case body, allowing the cover assembly to function as an independent module for both microphone and playback. In this embodiment, the earphone case not only stores wireless earphones but also allows the cover assembly to function independently as an earphone. During two-way communication, one person wears the wireless earphones while the other wears the cover assembly with the help of the magnetic component, reducing the distance limitation for communication and enabling high-quality voice interaction.

The invention provides an ultra-low time delay signal sequence conversion method and system, which can be widely applied to various time sequence conversion scenes, including hearing enhancement systems and equipment, such as hearing aid, denoising, simultaneous translation, sound conversion signal sequence, intelligent glasses, brain-computer systems and the like. According to the invention, the rapid high-fidelity noise elimination method is adopted, so that the limitation and difficulty in the traditional technology can be overcome. And for the problems of noise uncertainty and voice distortion in the sound related field, the high-quality voice can be recovered by recognizing the voice content as the intermediate language representation with high generalization, and meanwhile, the voice of the same speaker is synthesized by using a pre-trained artificial intelligence module. And the ultra-low time delay is realized by using a variable multi-partition block and a multi-head prediction mechanism in the process. Therefore, in the specific hearing enhancement field, the voice of the target speaker can be focused by using the voice separation technology, and the uncertainty of background noise is avoided.

The present disclosure provides a voice communication method, device and system, storage medium and electronic device, which relate to the field of voice communication technology. When the method is applied to a terminal, it includes: encoding the collected original voice signal, determining the first data stream and sending it to the server; in response to the second data stream returned by the server according to the first data stream, decoding the second data stream and determining the play voice signal; the bandwidth of the first data stream and the second data stream meet the bandwidth resource constraints of narrowband communication; using a trained deep learning model to optimize and reconstruct the play voice signal and determine the optimized voice signal. On the basis of meeting the bandwidth resource constraints of narrowband communication, the sending of the original language signal and the optimization of the play voice signal are realized, thereby completing high-quality voice communication.

The invention provides a voice recognition method, device and equipment and a readable storage medium, and relates to the technical field of voice recognition, and the method comprises the steps: obtaining historical audio data; obtaining the processed voice data; performing feature extraction to obtain a first voice feature and a second voice feature; when the similarity is greater than a first set threshold value, inputting preset target audio data into a preprocessing model for preprocessing to obtain target voice data; and obtaining a speech recognition result. According to the method, the historical voice data carrying the noise are input into the model for preprocessing, the processed data and the historical voice data not carrying the noise are subjected to feature comparison, and the parameters and the algorithm of the model are continuously optimized, so that the preprocessing model obtained by training can more effectively recognize and remove noise interference, and the noise interference can be effectively eliminated. A clearer and more accurate input signal is provided for a subsequent voice recognition model, it is ensured that only high-quality voice data enter a recognition process, and the recognition accuracy of the voice recognition model is remarkably improved.

This utility model relates to the field of audio acquisition equipment technology and discloses a microphone for classrooms, including a microphone body comprising a housing. This microphone for classrooms constructs a highly efficient dual noise reduction system by incorporating a noise-reducing cover and composite sound-absorbing cotton. The noise-reducing cover tightly wraps around the housing, utilizing its material properties to block most external environmental noise, such as noise from outside the window and footsteps outside the classroom. The composite sound-absorbing cotton, filled between the housing and the noise-reducing cover, further absorbs residual noise penetrating the cover while reducing noise generated by vibrations of internal components. This design allows the microphone to effectively filter out non-target sounds in complex classroom environments, significantly improving the clarity of target sounds such as teachers lecturing and students answering questions. It avoids the audio blurring problem caused by noise interference in traditional microphones, providing higher-quality sound materials for classroom recording, remote teaching, and other scenarios.

The invention provides a voice recognition method, device and equipment and a readable storage medium, and relates to the technical field of voice recognition, and the method comprises the steps: obtaining historical audio data; obtaining the processed voice data; performing feature extraction to obtain a first voice feature and a second voice feature; when the similarity is greater than a first set threshold value, inputting preset target audio data into a preprocessing model for preprocessing to obtain target voice data; and obtaining a speech recognition result. According to the method, the historical voice data carrying the noise are input into the model for preprocessing, the processed data and the historical voice data not carrying the noise are subjected to feature comparison, and the parameters and the algorithm of the model are continuously optimized, so that the preprocessing model obtained by training can more effectively recognize and remove noise interference, and the noise interference can be effectively eliminated. A clearer and more accurate input signal is provided for a subsequent voice recognition model, it is ensured that only high-quality voice data enter a recognition process, and the recognition accuracy of the voice recognition model is remarkably improved.

A high-quality voice signal processing device through removal of ambient noise based on multi-sensor signal fusion, includes: a voice microphone sensor that senses and outputs a speaker's voice signal; an accelerometer sensor that senses vibration of the speaker's vocal cords and outputs a signal; a noise reduction processing MCU that extracts a voice section according to vocal cord vibration using the output signal of the accelerometer sensor, synthesizes a low-frequency component of the accelerometer sensor and a low-frequency component of the voice microphone sensor at different synthesis ratios based on a level of noise extracted from the output signal of the voice microphone sensor using voice section information, and restores and outputs a voice signal by adding the synthesized low-frequency components and a high-frequency component of the voice microphone sensor; and a wireless communication module that externally outputs the restored voice signal.

The utility model discloses a self-adaptive voice noise reduction interphone comprising a PCB, the PCB is provided with a voice noise reduction module, a VHF transmit-receive module, a baseband module and a radio frequency module, the baseband module is connected with the voice noise reduction module and the radio frequency module, and the VHF transmit-receive module is connected with the baseband module. The voice noise reduction module receives audio signals and filters dynamic noise and hydrodynamic noise in the audio signals, the radio frequency module transmits the signals to the baseband module, and the radio frequency module is connected with the VHF transceiver module. The VHF transceiver module converts an audio signal into a radio frequency signal of a VHF frequency band and sends the radio frequency signal of the VHF frequency band from an interphone, and the baseband module is used for coding input digital data so as to modulate the digital data through the radio frequency module. According to the utility model, high-quality voice talkback can be realized by externally connecting the hearing aid without additionally changing channels, reducing volume and changing scenes, and the stability and reliability of communication are improved.

The present application realizes a signal generation processing device that realizes a voice synthesis processing or an image signal generation processing that can maintain the speed of the voice synthesis processing or the image signal generation and obtain a high-quality voice signal or an image signal. In the signal generation processing device, first to Nth sub-model sections respectively perform learning processing of learning models included in the first to Nth sub-model sections using noise levels included in different noise level ranges, thereby acquiring learned models. That is, in the signal generation processing device, processing can be performed in parallel for each sub-model section, and as a result, the learning processing can be performed at high speed. In addition, in the signal generation processing device, at the time of prediction processing, a sub-model section to be used for processing can be appropriately selected, and thus a high-precision voice synthesis processing or an image generation processing can be performed.