Voice keyword detection method based on complementary model score fusion

Abstract

The invention provides a voice keyword detection method based on complementary model score fusion. The method comprises the following steps of 1), introducing keyword modeling based on i-vector on thebasis of keyword modeling in an audio feature space, (2) self-adaptive segmented window shift: for a voice sample to be detected, intercepting a voice segment from the starting signal, obtaining thedistribution expression of the current segment in the voice feature space, calculating the similarity between the distribution expression and the keyword class attributes to obtain a class score sequence of the current segment, obtaining the window shift of the next segment according to the score of the current segment, processing segment by segment until the signal is ended, and dividing a voicesample to be detected into K segments, and 3) conducting score fusion by using the position of a keyword candidate point. According to the method, a keyword detection algorithm with certain complementarity is realized by adopting two different models, the score results of the two models are fused, the problem of voice keyword detection under the condition of a small training sample amount can be solved, and meanwhile, the keyword detection accuracy can be improved.

Description

technical field [0001] The invention relates to the field of continuous speech keyword recognition, in particular to a speech keyword detection method based on complementary model score fusion. Background technique [0002] Speech keyword detection is a special application of speech recognition technology, and its purpose is to detect whether a specific keyword is contained in continuous speech. At present, continuous speech keyword recognition technology has achieved rapid development and has been successfully popularized in many scenes in life. It has become an important research topic in the fields of voice control, voice retrieval, and security monitoring. [0003] There are three main traditional speech keyword detection techniques: sliding matching model, garbage model based on hidden Markov model and syllable grid network. The sliding matching model uses sliding windows to search for keywords on continuous speech, and uses dynamic time warping for matching calculatio...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to solve the problem of insufficient information expression of a single model, which leads to unreliable judgment, by using model evaluation and fusion with certain information expression complementary

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