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Single-channel voice separation method and device and electronic equipment

A speech separation, single-channel technology, applied in speech analysis, instruments, etc., to improve intelligibility, good separation effect, and reduce distortion rate

Active Publication Date: 2020-07-17
JIANGSU UNIV
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Problems solved by technology

However, temporal separation systems usually need to model extremely long input sequences, and need to mine the relationship between frames in the input sequence, which is a huge challenge for temporal separation methods

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  • Single-channel voice separation method and device and electronic equipment
  • Single-channel voice separation method and device and electronic equipment
  • Single-channel voice separation method and device and electronic equipment

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Embodiment Construction

[0032] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts are within the protection scope of the present invention.

[0033] see figure 1 , a single-channel speech separation method based on a self-attention mechanism and a two-way recurrent neural network, the method includes the following steps:

[0034] Step 1, the encoder receives the mixed speech signal of multiple people speaking, and extracts the features of the mixed speech signal:

[0035] Using a one-dimensional convolutional neural network as an encoder to extract features X∈R from a mixed speech signal of multiple people speaking N×L , the feature is a 2-D tensor, where R represents a set of real numbers, L is the number o...

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Abstract

The invention provides a single-channel voice separation method and device and electronic equipment, and the method comprises the steps: extracting mixed voice signal features through an encoder, segmenting the extracted voice signal features and splicing the voice signal features into a 3-D tensor; modeling the spliced 3-D tensor by using a double-path recurrent neural network fused with a self-attention mechanism, and learning a long-time dependency relationship between voice signals; overlapping and adding the modeled 3-D tensors, and restoring the 3-D tensors into sequence voice signal features; and reconstructing the sequence voice signal features into pure voice signals by using a decoder to obtain separated voice signals. According to the invention, the long-time voice signals are modeled with the purpose of improving the voice separation performance, the long-time dependence relation between the voice signals is fully mined, the separation effect is good, the voice distortion rate is effectively reduced, and meanwhile, the intelligibility of voice separation is improved.

Description

technical field [0001] The invention relates to the fields of speech signal processing, pattern recognition and the like, and in particular to a single-channel speech separation method, device and electronic equipment. Background technique [0002] Single-channel speech separation refers to separating the pure speech of each person from a mixed speech of multiple people, which is an important branch in the field of signal processing. It has many practical applications in the real world, such as: separating pure speech signals from mixed noise speech to improve the accuracy of speech recognition and speaker identification. In the fields of video conference transcription, hearing assistance, mobile communication, etc., single-channel speech separation has broad application prospects and practical significance. [0003] Traditional single-channel speech separation mainly uses non-negative matrix factorization and auditory scene analysis. The non-negative matrix factorization ...

Claims

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Application Information

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IPC IPC(8): G10L21/0272G10L25/30
CPCG10L21/0272G10L25/30
Inventor 毛启容陈静静钱双庆高利剑
Owner JIANGSU UNIV
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