Multilingual speech recognition model training method and device thereof, equipment and storage medium

Abstract

The invention discloses a multilingual speech recognition model training method, and relates to the field of artificial intelligence, and the method comprises the steps: carrying out the training of aspeech recognition model through a first language, and obtaining an initial speech recognition model; building an adaptive network function, and embedding the adaptive network function into a hiddenlayer of the initial speech recognition model to obtain an initial multilingual speech recognition model; performing model training on the initial multilingual speech recognition model through the speech data of the second language to obtain a training result; and iteratively updating the initial multilingual speech recognition model until the training result falls into a preset standard trainingresult range, and outputting the multilingual speech recognition model. In addition, the invention also relates to a blockchain technology, and the voice data of the first language and the voice dataof the second language can be stored in the blockchain. According to the invention, the adaptive network function is embedded into the hidden layer of the initial speech recognition model, so that thetraining efficiency of the multi-language speech recognition model can be improved.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, and in particular to a multilingual speech recognition model training method, device, equipment and storage medium. Background technique [0002] At present, speech recognition technology is very mature. Under the technical research of some speech recognition institutions, the recognition accuracy of the speech recognition model can reach 94.5%, which can be said to have reached the human auditory perception ability. However, this excellent speech recognition model is limited to a few widely used languages, such as English and French. At present, there are more than 5,000 languages ​​​​used by people all over the world, but only 10 languages ​​​​are widely used in these 5,000 languages. They are: Chinese, English, Russian, Spanish, Hindi, Arabic, Portuguese, Bengali, German and Japanese. For other languages, due to the small number of users, it is difficult to collect ...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present application is to propose a multilingual speech recognition model training method, device, computer equipment and storage medium to solve the problem that the existing multilingual speech recognition models require refined design of the model structure and low model training efficiency question

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