Abstract
Language recognition is essentially a pattern recognition problem, and all kinds of pattern recognition methods are used for language recognition research. For language recognition studied in this project, the highly effective speech feature parameters, acoustic model and language recognition classifier, the Chinese, Tibetan, Mongolian, uygur and training of acoustic model are established, so as to identify the voice input languages. In recent years, the deep learning theory has been applied in the field of speech recognition, and the DNN-HMM model has become the mainstream of acoustic modeling. This project studies Tibetan, Mongolian, Uygur emotion modeling of acoustic model and language model, training methods, studies the decoding algorithm, for continuous speech recognition of input speech, converts it to ethnic Chinese words.
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