End point detection method for voice without leading mute segment

A technology of endpoint detection and silent segment, applied in speech analysis, instruments, etc., can solve problems such as unavailability, endpoint errors, and performance degradation of double-threshold algorithms
CN105825871AActive Publication Date: 2016-08-03DALIAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
DALIAN UNIV OF TECH
Publication Date
2016-08-03

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Abstract

The invention relates to an end point detection method for voice without a leading mute segment, and belongs to the technical field of voice signal processing. The method comprises the following steps that S1) an LMS adaptive algorithm is used to filter the voice with noise; 2) the de-noised voice is changed from the time domain to the frequency domain; 3) an MFCC parameter of each frame is calculated; 4) the spectral entropy of each frame is calculated; 5) FCM is used to classify voice signals; and 6) the average spectral entropy of each classification in the step 5) is calculated, and voice signals and noise signals are marked. According to the method of the invention, it is not required to set a threshold, and end point detection error caused by that the threshold is set wrongly can be avoided; and compared with a monitored clustering method via a neural network and the like, sample training is not needed, calculation is simple and rapid, and the method is conducive to design of a real-time voice recognition system subsequently.
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Description

technical field

[0001] The invention relates to a method for detecting an endpoint of a speech without a leading silent segment, and belongs to the technical field of speech signal processing. Background technique

[0002] With the development of human-computer information interaction technology, speech recognition technology shows its importance. In speech recognition system, speech endpoint detection is one of the key technologies in speech recognition. Speech endpoint detection refers to finding the starting point and ending point of the speech part in the noisy continuous sound signal. Whether the endpoint detection is accurate or not will directly affect the performance of the speech recognition system. An effective endpoint detection method can not only detect voice endpoints correctly, but also reduce data processing time, save storage space and improve efficiency.

[0003] Due to different requirements, such as calculation accuracy, algorithm complexity, robustnes...

Claims

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