Chinese tone recognition method based on time frequency crest line-Hough transformation

Abstract

The invention provides a Chinese tone recognition method based on time frequency crest line-Hough transformation. Chinese tone recognition is converted into classification of the change trend of a line segment in a time frequency distribution diagram so that a new Chinese tone recognition method and technique can be acquired. The method includes the steps that firstly, final voice signals carrying Chinese tones are expressed through the SPWVD time frequency distribution diagram and tone information is shown through a group of similarly-parallel time frequency crest lines in the time frequency diagram; secondly, due to the fact that the main time frequency crest line is a region with larger energy in the diagram, the change trend of different tones is reflected, and in order to reduce the calculated amount, treatment such as binaryzation, thresholding and refining is conducted on the time frequency distribution diagram, and a center line segment of the main time frequency crest line reflecting the change trend of the tones is acquired; thirdly, Hough transformation is conducted on the time frequency distribution diagram containing the center line of the main crest line, so that the intercept and included angle parameters of the center line of the main crest line are acquired; finally, the tone type is judged according to the intercept and the included angle of the line segment and the coordinate values of a start point and an end point of the line segment.

Description

technical field [0001] The invention belongs to the technical field of tone recognition in speech synthesis and speech recognition. In the present invention, the final phonetic signal carrying Chinese tones is represented by a time-frequency distribution, and the tone information of Chinese is reflected in the ridge line variation trend in the time-frequency distribution image. After preprocessing such as thinning and thinning, the line segments reflecting the trend of tone change are obtained, and the Hough transform is performed on these line segments, and the tones of Chinese are recognized according to the Hough transform parameters. Background technique [0002] In addition to the non-stationary commonality of speech signals, Chinese speech signals also have tone features. Tone is one of the main attributes of Chinese, and it has functions such as word formation, meaning discrimination, and expression improvement. 30% of Chinese has the same sound but different tones. ...

AI Technical Summary

Problems solved by technology

The time-domain method has a small amount of calculation, but its anti-noise performance is poor and it is prone to frequency doubling or half-doubling. It is impossible for the pitch frequency trace extracted by one method to match the real pitch frequency trace completely.

In addition, after the tone features are extracted, classifiers such as support vector machines, Gaussian mixture models, and neural networks are generally used to identify them. It takes a training process to identify the tone. The algorithm is complex and the calculation time is long.

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