Differential-training-based voice wake-up customization optimization method and system

A technology of voice wake-up and optimization method, applied in speech analysis, voice recognition, instruments, etc., can solve the problem of inability to clearly distinguish wake-up words and non-wake words, and achieve good sequence-level non-wake word modeling, Improve the wake-up rate and improve the effect of sequence-level modeling

Active Publication Date: 2017-09-01
AISPEECH CO LTD
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Problems solved by technology

[0003] The present invention aims at the defects and deficiencies such as the inability to clearly distinguish between wake-up words and non-wake-up words in the prior art, or that can only be realized by customizing the speech model, thereby increasing the implementation cost and reducing the robustness, etc., and proposes a The customized voice wake-up optimization method and system based on discriminative training uses context-independent phoneme acoustic decoding to perform efficient search, thereby completing the confidence selection of wake-up words

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  • Differential-training-based voice wake-up customization optimization method and system
  • Differential-training-based voice wake-up customization optimization method and system
  • Differential-training-based voice wake-up customization optimization method and system

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Embodiment Construction

[0020] like figure 1 As shown, this embodiment relates to a customized voice wake-up optimization system based on discriminative training, including: a search network based on wake-up words, a decoding search module, an acoustic model module based on discriminative training, and a confidence discrimination module, wherein: search The network is connected to the decoding search module and transmits linguistic information for customized wake-up words. The acoustic model module is connected to the decoding search module and transmits the acoustic information score for modeling the signal. The decoding search module obtains the posterior probability through model speculation and outputs To the confidence level judging module, the confidence level judging module obtains the awakening judgment result by automatically estimating the threshold.

[0021] The acoustic model module specifically includes: labeling wake-up word modeling unit, wake-up word competition item modeling unit and...

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Abstract

The invention relates to a differential-training-based voice wake-up customization optimization method and system. After acoustic data with marks are given, neural network forward propagation is carried out by combining an initial neural-network-based acoustic model; a modeling probability for wake-up word marking is obtained by combining a marking sequence and a frame-by-frame acoustic probability; statistics is carried out on lots of texts to obtain a phoneme-level language model and a corresponding searching network is constructed; wake-up word competition item modeling is carried out based on the searching space of the phoneme-level language model and a frame-by-frame acoustic model, thereby obtaining a posterior probability; differential training of the acoustic model is carried out by combining the wake-up word competition item modeling and the wake-up word marking modeling; and the acoustic model obtained by the differential training determines whether to carry out a wake-up operation by comparison of a wake-up word confidence coefficient with an automatic estimation threshold value.

Description

technical field [0001] The present invention relates to a technology in the field of voice recognition, in particular to a method and system for optimizing customized voice wake-up based on discriminative training. Background technique [0002] The task of the customizable voice wake-up (Voice Wake-up) system is to automatically discover and locate some pre-specified command words (wake-up words) from a continuous speech. The customizable feature is reflected in the fact that the wake-up word detection model does not depend on the user-specified wake-up word, so that the user's wake-up word can be easily changed without modifying the model. The main voice wake-up techniques include the early dynamic time warping method, the current hidden Markov model-based method, and the deep learning-based method. Contents of the invention [0003] The present invention aims at the defects and deficiencies such as the inability to clearly distinguish between wake-up words and non-wake-...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/02G10L15/06G10L15/14G10L15/22
CPCG10L15/02G10L15/06G10L15/14G10L15/22
Inventor 俞凯陈哲怀
Owner AISPEECH CO LTD
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