Speech signal endpoint detection method based on dynamic cumulant estimation

An endpoint detection and voice signal technology, applied in voice analysis, voice recognition, instruments, etc., can solve the problems of concealing statistical characteristics of data, errors in statistical analysis results, and inability to improve estimation accuracy, etc.

Active Publication Date: 2015-07-29
ANHUI UNIVERSITY
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Problems solved by technology

Therefore, using all historical data for statistical analysis not only cannot improve the estimation accuracy, but may also cover up the real statistical characteristics of the data.
In addition, in the process of data collection in a real environment, random large-scale outlier interference will cause large errors in statistical analysis results
Since traditional online algorithms rely on all signal data, errors caused by outliers are highly transitive

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  • Speech signal endpoint detection method based on dynamic cumulant estimation
  • Speech signal endpoint detection method based on dynamic cumulant estimation
  • Speech signal endpoint detection method based on dynamic cumulant estimation

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Embodiment Construction

[0073] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0074] see figure 1 , is a structural schematic diagram of the sliding window of the present invention. In this embodiment, the sliding window intercepts the original sample data through a rectangular window, in order to obtain the same length of data to be processed at any time, and the estimation of the cumulative amount is based on the L sample data in the sliding window, sliding one sample at a time Point to update the data in the window, and then re-estimate the cumulative quantity, so as to realize the dynamic estimation of the cumulative quantity.

[0075] Any two data sets x a and x b , the correspondin...

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Abstract

The invention discloses a speech signal endpoint detection method based on dynamic cumulant estimation, including sliding window-based high-order cumulant recursive computation and sliding window kurtosis-based endpoint detection. The sliding window-based high-order cumulant recursive computation includes: adding a rectangular window to original sample data, subjecting intra-window data to cumulant estimation, updating the intra-window data each time when one sample point is slid, and thus dynamically estimating the cumulant. The sliding window kurtosis-based endpoint detection includes: computing sliding window kurtosis and energy features by the use with the sliding window-based high-order cumulant recursive computation, thus subjecting speech signals to endpoint detection. Compared with the prior art, the method has the advantages that endpoint detection is based on sliding window kurtosis and energy double-threshold, the sliding window kurtosis is highly sensitive to the start point of a speech segment, resistance to noise interference is better, and the method is of better robustness in the noise environment.

Description

technical field [0001] The invention relates to the fields of statistical analysis of data and signal processing, in particular to a method for detecting endpoints of speech signals based on dynamic cumulant estimation. Background technique [0002] With the development of human-computer interaction technology, speech recognition has become the focus of research in the field of artificial intelligence and pattern recognition. Speech is the most important and convenient way for human beings to transmit information, and it is also one of the most direct ways to realize human-computer interaction. It is of great practical significance to allow machines to accurately recognize voice commands and perform corresponding operations. Related research has broad application prospects in many fields such as medicine, military and industry. As the front-end processing of speech recognition, the goal of speech endpoint detection is to distinguish the voiced segment and the unvoiced segme...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/04
Inventor 吴小培吕钊罗雅琴张超周蚌艳张磊郭晓静高湘萍
Owner ANHUI UNIVERSITY
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