A method and system for end-to-end speech emotion recognition

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, and achieve the effect of improving accuracy, precision and accuracy.

Active Publication Date: 2021-06-11
FOCUS TECH
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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

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  • A method and system for end-to-end speech emotion recognition
  • A method and system for end-to-end speech emotion recognition
  • A method and system for end-to-end speech emotion recognition

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Embodiment Construction

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

[0057] figure 1 It is a schematic structural diagram of a speech emotion recognition system in an exemplary embodiment of the present invention, and 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 sentence voice data and emotional labels in the original data set, and extract phoneme features and cepstral features of sentence voice; according to different extracted features, this module includes phoneme feature extraction submodules and cepstrum Feature extraction submodule; the phoneme feature extraction submodule is used to extract the phoneme feature of the sentence voice data, and completes the conversion of the phoneme sequence to the phoneme vector sequence; the cepstrum feature extraction submo...

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Abstract

The invention discloses an end-to-end speech emotion recognition method and system, which is characterized in that it includes phoneme feature extraction of speech data; cepstrum feature extraction of speech data; phoneme vector sequence and cepstrum feature are aligned in units of files, as Input, use the deep neural network for end-to-end speech emotion recognition model training; when the model is deployed, resampling and effective speech segment detection for any input speech data. Using the above feature extraction process and recognition model, end-to-end recognition of voice data can be performed, with higher efficiency and more accurate prediction.

Description

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

Claims

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Application Information

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Patent Type & Authority Patents(China)
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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