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Acoustic modeling of sentence stress using differential features between syllables for English rhythm learning system development.

, , , and . INTERSPEECH, page 745-748. ISCA, (2002)

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Improving hmm-based extractive summarization for multi-domain contact center dialogues., , , , , , , , , and . SLT, page 61-66. IEEE, (2010)Efficient data selection for spoken document retrieval based on prior confidence estimation using speech and context independent models., , , , and . SLT, page 200-205. IEEE, (2010)Efficient prior and incremental beam width control to suppress excessive speech recognition time based on score range estimation., , , , , and . SLT, page 125-130. IEEE, (2012)Efficient data selection for speech recognition based on prior confidence estimation using speech and monophone models., , , , and . Comput. Speech Lang., 28 (6): 1287-1297 (2014)Likability Estimation of Call-center Agents by Suppressing Annotator Variability., , , , and . APSIPA, page 911-916. IEEE, (2019)Speech Data Clustering Based on Phoneme Error Trend for Unsupervised Acoustic Model Adaptation., , , , and . INTERSPEECH, page 1760-1763. ISCA, (2012)Fast unsupervised adaptation based on efficient statistics accumulation using frame independent confidence within monophone states., , , , , and . Comput. Speech Lang., 27 (1): 369-379 (2013)Does the Lombard Effect Improve Emotional Communication in Noise? - Analysis of Emotional Speech Acted in Noise., , , , and . INTERSPEECH, page 3292-3296. ISCA, (2019)Rapid response and robust speech recognition by preliminary model adaptation for additive and convolutional noise., , , and . INTERSPEECH, page 965-968. ISCA, (2005)Hierarchical LSTMs with Joint Learning for Estimating Customer Satisfaction from Contact Center Calls., , , , and . INTERSPEECH, page 1716-1720. ISCA, (2017)