Voice detection method under noise condition

Abstract

The invention provides a voice detection method under noise condition, and belongs to the technical fields of digital signal processing, computer artificial intelligence and pattern recognition. The method comprises the following steps of: converting input signals to a frequency domain, and dividing into subbands; calculating a power spectrum of each subband to form a subband power spectrum; calculating mean-square deviation of the subband power spectrum of each frame, and comparing the mean-square deviation serving as a detection characteristic with an adaptive voice detection threshold to determine whether the current frame contains voice signals; and according to a detection result, adopting a certain endpoint determination strategy to determine an initial position and an ending position of a voice segment.

Description

technical field

[0001] The invention relates to a digital signal processing, computer artificial intelligence and pattern recognition technology, in particular to a method for using a computer to detect voice in a signal. Background technique

[0002] The accuracy of speech detection determines the performance of the entire speech processing system to a large extent. People have done a lot of research on speech detection and proposed many various methods. For example, based on short-term energy and short-time spectrum energy , short-term zero-crossing rate and other speech detection algorithms. But these characteristic parameters are sensitive to background noise and cannot describe the characteristics of speech well. Like short-term energy and short-term zero-crossing rate, they are not enough when the signal-to-noise ratio is low. To distinguish speech and background noise. Speech detection algorithms based on linear prediction coefficients, cepstral coefficients, and pitc...

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