Voice anomaly detection method based on sound source characteristics

An anomaly detection and speech technology, applied in speech analysis, instruments, etc., can solve the problems of low discrimination, lack of stability and robustness, and inability to classify acoustic features, so as to improve accuracy and reliability, and protect life and property. safe effect

Inactive Publication Date: 2018-05-25
HOHAI UNIV CHANGZHOU
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AI Technical Summary

Problems solved by technology

[0004] However, the variant speech under mental stress, especially the variant speech under multi-tasking brain load pressure, has a relati

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  • Voice anomaly detection method based on sound source characteristics
  • Voice anomaly detection method based on sound source characteristics
  • Voice anomaly detection method based on sound source characteristics

Examples

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Embodiment 1

[0069] We used a database collected by Fujitsu Corporation containing speech samples of 11 speakers (4 male and 7 female). In order to simulate the specific situation of psychological stress generation, three different tasks were set up for the speaker, carried out during the telephone conversation with the operator, to simulate the situation of stress in the telephone.

[0070] The three tasks involved were (A) highly focused (the speaker was asked to complete tasks that included solving logic puzzles and finding the difference between two pictures); (B) time pressure (the speaker was asked to answer questions under time pressure); ( C) Risky Behavior (taking risky tasks to assess the speaker's desire for monetary gain). For each speaker, there are four dialogues with different tasks. In two dialogues, the speakers were asked to complete tasks within a limited time, while in the other dialogues, there were no tasks and chatting was easy.

[0071] The parts taken from the sp...

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Abstract

The invention discloses a voice anomaly detection method based on sound source characteristics. The method comprises the following steps that voice data is collected in real time through a sensor; theobtained voice segment data is preprocessed; iterative self-adaptive inverse filtering is conducted on the voice data of a voice segment to obtain glottis wave signals; characteristic parameters areextracted from the glottis wave signals, and amplitude quotient and glottal closure time ratio data are normalized; extracted characteristic data is input into an ideal SVM model for classification; classification labels are obtained and used for judging conditions of speakers, and condition labels of the speakers are output and transmitted to an execution module for feedback. The method has the advantages that as for stressful voice under mental stress, an identification method for extracting acoustic characteristic parameters lacking physical significance on the basis of a traditional linearvoice generation module is got rid of, and a sound source estimation module is established; a voice generation inverse filtering technology is used for analyzing and extracting characteristic parameters based on human vocal cord vibration to carry out abnormal voice detection.

Description

technical field [0001] The invention relates to a voice abnormality detection method based on sound source characteristics, and belongs to the technical field of intelligent voice. Background technique [0002] Stress is the body's natural response to physical, mental, or emotional stimuli. When we are exposed to these stimuli, the brain releases alcohols and peptides into the body, causing a stress response. This continuous anxiety about work will be reflected on the vocal organs, which will cause changes in a series of parameters such as vocal frequency and pronunciation speed. These changes are of great significance in many fields of speech signal processing, such as variant speech recognition, emotion recognition, etc. [0003] An important manifestation of stress is the voice of the speaker when speaking, which has become a very important factor affecting the production of voice. When the surrounding environment or the speaker's own conditions change abnormally, or be...

Claims

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Application Information

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IPC IPC(8): G10L25/51G10L25/03G10L25/27G10L25/45
CPCG10L25/03G10L25/27G10L25/45G10L25/51
Inventor 姚潇白文松李伟亮徐宁李旭蒋爱民刘小峰张学武
Owner HOHAI UNIV CHANGZHOU
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