Chinese Academy of Sciences

Huawei Technologies Co., Limited

Jiaming Xu

Lei Zhang

Yue Lang

Bo Xu

Lei Qin

Henghui Lu

Jing Shi

Jian Cui

Yating Huang

Yiqun Yao

Churonggui Sa

Yunfan Du

This application provides a voice control method and apparatus, a wearable device, and a terminal. The method includes: obtaining voice information of a user; obtaining identity information of the user based on a first voiceprint recognition result of a first voice component of the voice information, a second voiceprint recognition result of a second voice component of the voice information, and a third voiceprint recognition result of a third voice component of the voice information, where the first voice component is captured by an in-ear voice sensor of a wearable device, the second voice component is captured by an out-of-ear voice sensor of the wearable device, and the third voice component is captured by a bone vibration sensor of the wearable device; and executing an operation instruction when the identity information of the user matches the preset identity information.

Voice control method and apparatus

A speech separation method is provided, and relates to the field of speech. The method includes: obtaining, in a speaking process of a user, audio information including a user speech and video information including a user face; coding the audio information to obtain a mixed acoustic feature; extracting a visual semantic feature of the user from the video information; inputting the mixed acoustic feature and the visual semantic feature into a preset visual speech separation network to obtain an acoustic feature of the user; and decoding the acoustic feature of the user to obtain a speech signal of the user. An electronic device, a chip, and a computer-readable storage medium are provided.

Speech separation method, electronic device, chip, and computer- readable storage medium

Disclosed are a target speaker separation system, an electronic device and a storage medium. The system includes: first, performing, jointly unified modeling on a plurality of cues based a masked pre-training strategy, to boost the inference capability of a model for missing cues and enhance the representation accuracy of disturbed cues; and second, constructing a hierarchical cue modulation module. A spatial cue is introduced into a primary cue modulation module for directional enhancement of a speech of a speaker; in an intermediate cue modulation module, the speech of the speaker is enhanced on the basis of temporal coherence of a dynamic cue and an auditory signal component; a steady-state cue is introduced into an advanced cue modulation module for selective filtering; and finally, the supervised learning capability of simulation data and the unsupervised learning effect of real mixed data are sufficiently utilized.

Target speaker separation system, device and storage medium

The method of the present disclosure includes: obtaining an image to be processed and a question text corresponding to the image; using an optimized dialogue model to encode the image into an image vector and encode the question text into a question vector; generating a state vector based on the image vector and the question vector; decoding the state vector to obtain and output an answer text. A discriminator needs to be introduced in an optimization process of the optimized dialogue model. The dialogue model and the discriminator are alternately optimized until a value of a hybrid loss function of the dialogue model and a value of a loss function of the discriminator do not decrease or fall below a preset value, thereby accomplishing the optimization process.

Autonomous evolution intelligent dialogue method, system, and device based on a game with a physical environment

A speech extraction method based on the supervised learning auditory attention includes: converting an original overlapping speech signal into a two-dimensional time-frequency signal representation by a short-time Fourier transform to obtain a first overlapping speech signal; performing a first sparsification on the first overlapping speech signal, mapping intensity information of a time-frequency unit of the first overlapping speech signal to preset D intensity levels, and performing a second sparsification on the first overlapping speech signal based on information of the preset D intensity levels to obtain a second overlapping speech signal; converting the second overlapping speech signal into a pulse signal by a time coding method; extracting a target pulse from the pulse signal by a trained target pulse extraction network; converting the target pulse into a time-frequency representation of the target speech to obtain the target speech by an inverse short-time Fourier transform.

Speech extraction method, system, and device based on supervised learning auditory attention

An auditory selection method based on a memory and attention model, including: step Sencoding an original speech signal into a time-frequency matrix; step Sencoding and transforming the time-frequency matrix to convert the matrix into a speech vector; step Susing a long-term memory unit to store a speaker and a speech vector corresponding to the speaker; step Sobtaining a speech vector corresponding to a target speaker, and separating a target speech from the original speech signal through an attention selection model. A storage device includes a plurality of programs stored in the storage device. The plurality of programs are configured to be loaded by a processor and execute the auditory selection method based on the memory and attention model. A processing unit includes the processor and the storage device.

Growing community of inventors

Beijing, China

Jiaming Xu