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Many studies have shown that deep learning outperforms traditional machine learning methods in many applications. To prevent overfitting, a huge number of training samples is usually required in training process of deep learning. However, collecting such a large dataset is time-consumed and costly. Recently, several methods have been proposed to effectively learn the models with a limited number of...
This paper establishes a speaker-independent pronunciation recognition and assessment system with 673 words for mandarin Chinese under the background of a Chinese learning system framework. The recognition part is based on HTK using HMM (Hidden Markov Models) and improved in the aspect of acoustic model. Making use of the recognition results and the log-likelihood obtained from the Viterbi coding,...
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