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Tibetan Weizang dialect spoken language recognition method based on deep time delay neural network

A neural network and spoken language recognition technology, applied in speech recognition, speech analysis, instruments, etc., can solve the problems of large differences in pronunciation characteristics and need to be improved, so as to increase diversity, increase recognition accuracy and generalization performance, and improve recognition. effect of effect

Active Publication Date: 2021-06-11
TIANJIN UNIV
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AI Technical Summary

Problems solved by technology

However, due to the large difference between the pronunciation characteristics of the source language and the Tibetan language, the effect of this technical solution still needs to be improved.

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  • Tibetan Weizang dialect spoken language recognition method based on deep time delay neural network
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  • Tibetan Weizang dialect spoken language recognition method based on deep time delay neural network

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specific Embodiment approach

[0057] The present invention is a technical scheme of a Tibetan U-Tibetan dialect spoken language recognition model based on a deep time-delay neural network. The construction work is mainly based on the Linux system experimental environment and the kaldi speech recognition toolbox, and some steps need to use GPU to speed up the operation. The specific implementation method comprises the following steps:

[0058] Step one, prepare the Tibetan audio dataset and then augment it with augmentation techniques. Its operation process is mainly divided into the following aspects:

[0059] First, prepare the acoustic training data. The Tibetan audio data set used when carrying out the model training experiment in the present invention is divided into two parts: a part is the small-scale audio data set of Tibetan U-Tibet dialect, about 36 hours long; The audio data sets of the three Tibetan dialects, Amdo dialect and Amdo dialect, are about 200 hours long. Due to the small size of th...

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Abstract

The invention relates to the technical field of deep learning, signal processing, speech recognition, feature extraction, pronunciation and the like, aims at improving the overall effect of a Tibetan Weizang dialect spoken language recognition model in allusion to spoken language application scenes of Tibetan Weizang dialects, and provides a Tibetan Weizang dialect spoken language recognition method based on a deep time delay neural network. An audio data set mixed by three Tibetan dialects is adopted, an original audio data set is expanded through speed disturbance, noise adding and reverberation methods, the expanded data set is utilized to train the deep time delay neural network based on a chained chain model of an open-source speech recognition toolbox kaldi, the deep time delay neural network serves as a Tibetan acoustic model, and the acoustic model is trained for the second time by using the part of the Weizang dialect in the audio data so as to obtain a deep time delay neural network acoustic model for the Weizang dialect. The method is mainly applied to Tibetan Weizang dialect spoken language recognition occasions.

Description

technical field [0001] The present invention relates to technical fields such as deep learning, signal processing, speech recognition, feature extraction, phonology, etc., and combines data augmentation technology with deep neural network technology, aiming at the application scenarios of Tibetan U-Tibetan dialects, targeted To train and adjust the main acoustic model and language model part, so as to achieve the purpose of building a Tibetan U-Tibetan dialect spoken speech recognition system with better effect. Background technique [0002] In today's era, artificial intelligence has become the frontier and hot spot of research in the technology industry, and various artificial intelligence technologies have gradually begun to land and enter people's lives. Speech recognition is one of the very important technical fields. Speech recognition technology is a technology that allows computers to hear people's language and convert it into corresponding text content. The develop...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/00G10L15/02G10L15/06G10L15/14G10L15/16G10L15/26G10L25/24G10L25/69
CPCG10L15/005G10L15/02G10L15/063G10L15/144G10L15/16G10L15/26G10L25/24G10L25/69G10L2015/025
Inventor 魏建国何铭徐君海
Owner TIANJIN UNIV
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