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End-to-end speech emotion recognition method and system

A speech emotion recognition and speech technology, applied in speech analysis, instruments, etc., can solve problems such as inefficiency and inability to meet the needs of intelligent systems

Active Publication Date: 2019-08-06
FOCUS TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In recent years, with the popularization of computers and the rapid development of artificial intelligence, traditional inefficient human-computer interaction methods can no longer meet the needs of various intelligent systems

Method used

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  • End-to-end speech emotion recognition method and system
  • End-to-end speech emotion recognition method and system

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Embodiment Construction

[0056] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments.

[0057] figure 1 It is a schematic structural diagram of a speech emotion recognition system according to an exemplary embodiment of the present invention. The system structure includes a data set production module, a model training module, and a speech emotion recognition module;

[0058] The data set production module is used to extract the sentence speech data and emotion tags in the original data set, and extract the phoneme features and cepstrum features of the sentence speech; according to the different extracted features, the module includes a phone feature extraction submodule and cepstrum The feature extraction submodule; the phoneme feature extraction submodule is used to extract the phoneme features of the sentence speech data to complete the conversion of the speech phoneme sequence to the phoneme vector sequence; the cepstrum feature extrac...

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Abstract

The invention discloses an end-to-end speech emotion recognition method and system. The method comprises the steps: extracting the phoneme features of speech data; extracting cepstrum features of thespeech data; aligning the phoneme vector sequence and the cepstrum feature by taking a file as a unit, taking the phoneme vector sequence and the cepstrum feature as input, and performing end-to-end speech emotion recognition model training by utilizing a deep neural network; when the model is deployed, carrying out resampling and effective speech segment detection on any input speech data. By using the feature extraction process and the recognition model, end-to-end recognition can be performed on the speech data, the efficiency is higher, and the prediction is more accurate.

Description

Technical field [0001] The present invention relates to the field of speech emotion recognition, in particular to a method and system for end-to-end speech emotion recognition. Background technique [0002] Computer's speech emotion recognition ability is an important part of computer emotional intelligence, and it is the key prerequisite for realizing natural human-computer interaction interface. [0003] The real speech emotion recognition related research first appeared in the mid-1980s. In 1985, Professor Minsky put forward the idea of ​​"making computers have emotional capabilities"; in the early 1990s, the MIT Multimedia Laboratory constructed an "emotion editor" The "device" collects various emotion signals, initially recognizes emotions, and makes simple reactions; in 1999, Moriyama proposed a linear correlation model between speech and emotion, and based on this, built an image collection that can recognize user emotions in an e-commerce system System voice interface. On...

Claims

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Application Information

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IPC IPC(8): G10L25/63G10L25/24G10L25/30G10L25/03
CPCG10L25/03G10L25/24G10L25/30G10L25/63
Inventor 滕炜倪俊辉孙佳伟席晓燕
Owner FOCUS TECH
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