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Method for recognizing emotion points of Chinese pronunciation based on sound-track modulating signals MFCC (Mel Frequency Cepstrum Coefficient)

An emotion and signal technology, applied in the information field, can solve the problem of low average recognition rate of emotion points

Inactive Publication Date: 2013-12-04
BEIHANG UNIV
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Problems solved by technology

[0003] By directly extracting features from the voice data, then training, modeling, and recognizing the low average recognition rate of emotion points, the present invention proposes a method for improving the average recognition rate of emotion points in Chinese speech

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  • Method for recognizing emotion points of Chinese pronunciation based on sound-track modulating signals MFCC (Mel Frequency Cepstrum Coefficient)
  • Method for recognizing emotion points of Chinese pronunciation based on sound-track modulating signals MFCC (Mel Frequency Cepstrum Coefficient)
  • Method for recognizing emotion points of Chinese pronunciation based on sound-track modulating signals MFCC (Mel Frequency Cepstrum Coefficient)

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Embodiment Construction

[0048] The technical solution of the present invention will be further elaborated below in conjunction with the accompanying drawings.

[0049] figure 1 It is a flow chart of feature extraction using electroglottogram signals and speech signals, training models and identifying emotional points. It is mainly divided into two parts: the acquisition of Chinese speech emotional points and the recognition of Chinese speech emotional points.

[0050] One, the acquisition of Chinese speech emotion point, the method steps are as follows:

[0051] Step 1. Formulate the recording specifications of the emotional voice database, the specific rules are as follows;

[0052] (1) Speakers: 10 people aged between 20 and 25 years old with a bachelor's degree, 5 males and 5 females.

[0053] (2) Speech content: 28 interjections were selected as emotional points, and each emotional point was recorded 3 times during the experiment.

[0054] (3) Emotion classification: anger, joy, sadness, surpr...

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Abstract

The invention provides a method capable of increasing the average recognition rate of emotion points. The method comprises the following steps of: making specifications of emotion data of an electroglottography and voice database; collecting the emotion data of the electroglottography and voice data; carrying out subjective evaluation on the collected data, and selecting one set of data subset as a study object; carrying out preprocessing on electroglottography signals and voice signals, and extracting short-time characteristics and corresponding statistical characteristics in the voice signals and MEL frequency cepstrum coefficient SMFCC; carrying out fast Fourier transform on the electroglottography signals and the voice signals, then dividing the electroglottography signals and the voice signals, and after dividing, obtaining MEL frequency cepstrum coefficient TMFCC; and respectively using different characteristic combination for carrying out experiment, and solving the average recognition rate of 28 emotion points under different characteristic combinations when a speaker is related and not related. The experimental result shows that by adoption of TMFCC characteristics, the average recognition rate of the emotion points can be increased.

Description

(1) Technical field: [0001] The invention relates to a method for improving the average recognition rate of emotion points in Chinese speech based on channel modulation signal MFCC, which belongs to the field of information technology. (two) background technology: [0002] Speech emotion recognition is to extract the speaker's emotional state from the speech signal. According to the speech excitation modulation model, the speech signal generation includes glottal excitation and vocal tract modulation. Glottal excitation determines the change of speech prosody and plays an important role in speech emotion recognition. Vocal tract modulation mainly determines the speech content, and each vowel corresponds to a different formant, reflecting different vocal tract shape information. Chinese is a tonal speech, most syllables are composed of initials and finals, syllables composed of the same initials and finals have different meanings and express different emotions depending on ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G10L17/26G10L25/63G10L15/14G10L17/00
Inventor 毛峡魏鹏飞
Owner BEIHANG UNIV