Method, apparatus and system for identifying dispersed voice emotions based on emotion dimension prediction

A speech emotion recognition and speech technology, which is applied in the field of affective computing, can solve problems such as difficult to meet the requirements of emotional state recognition

Active Publication Date: 2018-01-26
中科极限元(杭州)智能科技股份有限公司
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Problems solved by technology

[0005] In order to solve the above-mentioned problems in the prior art, that is, in order to solve the problem that the recognition of the emotional state by the existing speech emotion recognition method is difficu

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  • Method, apparatus and system for identifying dispersed voice emotions based on emotion dimension prediction
  • Method, apparatus and system for identifying dispersed voice emotions based on emotion dimension prediction
  • Method, apparatus and system for identifying dispersed voice emotions based on emotion dimension prediction

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Embodiment Construction

[0030] Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

[0031] Such as figure 1 As shown, it is a schematic flow chart of a discrete speech emotion recognition method based on emotional dimension prediction according to an embodiment of the present invention, including:

[0032] Step S1: Extract the basic acoustic features of speech, and combine the basic acoustic features into speech emotion features;

[0033] In practical applications, in order to better reflect the features contained in speech, multiple parameters are often used as the basic acoustic features of speech. Among them, the basic acoustic features include short-term energy jitter, pitch frequency, zero-crossing rate, 0 to 12th-orde...

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Abstract

The invention relates to the field of emotion computing, and in particular to a method, apparatus and system for identifying dispersed voice emotions based on emotion dimension prediction, aiming at overcoming the difficulty of current voice emotion identification methods in identifying emotions. According to the invention, the method includes the following steps: extracting the basic acoustic features of a voice, combining the basic acoustic features to form voice emotion features, performing windowing processing on the voice emotion features, after obtaining global voice emotion features, performing prediction to obtain emotion dimension information, combining the global voice emotion features and the emotion dimension information, identifying the dispersed voice emotions, and obtainingthe result from voice emotion identification. According to the invention, the method, by integrating the emotion dimension information to the global voice emotion features, increases the dimension ofthe voice emotion features, and increases the accuracy of dispersed voice emotion identification. The invention also provides an apparatus and system for identifying the dispersed voice emotions basedon emotion dimension prediction, and the apparatus and the system have the aforementioned beneficial advantages.

Description

technical field [0001] The present invention relates to the field of emotion computing, and specifically provides a discrete speech emotion recognition method, device and system based on emotion dimension prediction. Background technique [0002] With the development of artificial intelligence, the status of affective computing is becoming more and more important. Affective computing tries to endow machines with the ability to observe, understand and generate various emotions, making machines more human-like with emotions. Speech, as an important transmission medium in human communication, contains a lot of emotional information. Speech emotion recognition can improve the ability of machines to understand human voice emotions, and thus be more widely used in human-computer dialogue, making human-computer interaction more natural harmonious. [0003] Speech emotion recognition mainly includes two steps of feature extraction and classifier classification. At present, there is...

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Application Information

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IPC IPC(8): G10L25/63G10L25/45G10L25/12G10L25/24G10L25/60G10L15/08
Inventor 陶建华黄健李雅
Owner 中科极限元(杭州)智能科技股份有限公司
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