Context-Dependent Deep-Neural-Network HMMs, or CD-DNN-HMMs, combine the classic arti?cial-neural-network HMMs with traditional context-dependent acoustic mod- eling and deep-belief-network pre-training. CD-DNN-HMMs greatly outperform conven- tional CD-GMM (Gaussian mixture model) HMMs: The word error rate is reduced by up to one third on the di?cult benchmarking task of speaker-independent single-pass transcription of telephone conversations.

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In  ICML 2012

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