Method and device for multilingual hybrid model establishment and data acquisition, and electronic equipment

Abstract

Embodiments of the invention provide a method and device for multilingual hybrid model establishment and data acquisition, and electronic equipment. The method includes determining a modeling unit ofan acoustic model according to a speech unit contained by multilanguage, and establishing the acoustic model based on a deep neural network, wherein the modeling unit is the context free speech unit;obtaining multilingual hybrid speech training data, converting a hybrid speech signal in the multilingual hybrid speech training data into an eigenvector sequence, and converting a hybrid labelling text corresponding to the hybrid speech signal into a hybrid label sequence of the modeling unit based on the acoustic model; training the acoustic model by using the eigenvector sequence and the hybridlabel sequence; obtaining multilingual hybrid corpus data to train a language model; and establishing a multilingual hybrid speech recognition system according to the acoustic model and the languagemodel. According to the embodiments, recognition accuracy of speech data mixing multiple languages can be enhanced.

Description

technical field [0001] The invention relates to the technical field of speech recognition, in particular to a multilingual mixed model establishment, data acquisition method and device, and electronic equipment. Background technique [0002] Speech data is divided into speech data in multiple languages, and speech recognition technology refers to the process of converting a piece of speech data of different types into text. [0003] At present, in order to be able to realize the speech recognition of multiple languages, the speech recognition system of each language is usually trained separately by using the data of each language first, and the speech recognition system for each language is obtained. Here, speech recognition The system includes an acoustic model and a language model; the speech recognition systems for different languages ​​are connected in parallel to obtain a hybrid speech recognizer. [0004] Based on the hybrid speech recognizer, when the speech data is ...

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Problems solved by technology

[0005] Based on the above situation, it can be seen that in the prior art, better recognition results can be obtained for speech data that are independently formed into sentences in multiple languages, but for a sentence in which multiple languages ​​are mixed, for example, Chinese and English are mixed in a sentence. Inability to obtain a good recognition result

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