Cross-language end-to-end speech recognition method for low resource Tujia language

Abstract

The invention discloses a cross-language end-to-end speech recognition method for the low resource Tujia language. The method comprises the following steps: preprocessing the Tujia language data; constructing a cross-language Tujia language corpus; establishing a unified coding dictionary of Chinese international phonetic alphabets and national international phonetic alphabets; establishing a cross-language end-to-end Tujia speech recognition model; and using a join temporal classification model and performing decoding under the action of the coding dictionary so as to obtain the recognition result. The recognition model with higher generalization is constructed by taking advantage of sufficient major language data and combining the idea of transfer learning so as to improve the accuracy of Tujia language speech recognition.

Description

technical field

[0001] The invention belongs to the field of speech recognition and relates to a cross-language end-to-end speech recognition method for low-resource Tujia languages. Background technique

[0002] With the development of Internet technology and the improvement of computer computing power and hardware, speech recognition technology has once again ushered in a new upsurge, especially in recent years, deep learning has once again ignited the enthusiasm of scientists for speech recognition technology. Speech recognition technology has a wide range of applications. With the development of artificial intelligence, speech recognition technology not only includes functions such as voice dialing, voice navigation, voice document retrieval, simple dictation data entry, etc., but also includes intelligent traffic control, indoor equipment control, etc. , smart city and other applications. If the speech recognition technology can be well developed, it is believed that i...

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