Cross-Entropy Training of DNN Ensemble Acoustic Models for Low-Resource ASR.

IEEE/ACM Transactions on Audio, Speech, and Language Processing(2018)

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摘要
Deep neural networks (DNNs) have shown a great promise in exploiting out-of-language data, particularly for under-resourced languages. The common trend is to merge data from various source languages to train a multilingual DNN and then reuse the hidden layers as language-independent feature extractors for a low-resource target language. While there is a consensus that using as much data from vario...
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关键词
Training,Acoustics,Hidden Markov models,Feature extraction,Interpolation,Neural networks,Training data
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