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Combination of multiple acoustic models with unsupervised adaptation for lecture speech transcription.

, , , , , , and . Speech Commun., (2016)

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Efficient multi-lingual unsupervised acoustic model training under mismatch conditions., , , and . SLT, page 24-29. IEEE, (2014)Combination of multiple acoustic models with unsupervised adaptation for lecture speech transcription., , , , , , and . Speech Commun., (2016)The NICT ASR system for IWSLT 2013., , , , , , and . IWSLT (Evaluation Campaign), (2013)Incorporating tone features to convolutional neural network to improve Mandarin/Thai speech recognition., , and . APSIPA, page 1-5. IEEE, (2014)Effectiveness of Feature-selected LBP-TOP for Emotional Estimation by Micro-expression., , , , and . SCIS/ISIS, page 1-5. IEEE, (2020)Characteristics of LBP-TOP Feature for Emotional Estimation by Micro-expression., , , , and . ISCIT, page 89-91. IEEE, (2021)The NCT ASR system for IWSLT 2014., , , , , and . IWSLT (Evaluation Campaign), (2014)Comparative Study of Feature Extraction Method for Emotional Classification by Micro-expressions., , , , and . APSIPA ASC, page 1781-1785. IEEE, (2021)Cross-lingual acoustic model adaptation based on transfer vector field smoothing with MAP., , , , and . INTERSPEECH, page 3322-3326. ISCA, (2013)