Abstract
The study of a system for Vietnamese continuous digit recognition is described. The CSLU Toolkit was used to develop and implement hybrid HMM/ANN recognition systems. Experiments were done with a corpus of 442 sentences with 2340 words, which were extracted from two telephone-speech corpora: “22 Language v1.2” and “Multi-Language Telephone Speech v1.2”. In our experiments, a context-dependent phoneme recognizer has achieved better recognition performance than a context-dependent demi-syllable recognizer and a context-independent phoneme recognizer. Among feature sets applied to the context-dependent phoneme recognizer, the set of 12 PLP features with CMS, energy and corresponding delta values has achieved the best recognition result (96.83% word accuracy and 87.67% sentence correct).
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© 2003 Springer-Verlag Berlin Heidelberg
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Duc, D.N., Hosom, JP., Mai, L.C. (2003). HMM/ANN System for Vietnamese Continuous Digit Recognition. In: Chung, P.W.H., Hinde, C., Ali, M. (eds) Developments in Applied Artificial Intelligence. IEA/AIE 2003. Lecture Notes in Computer Science(), vol 2718. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45034-3_48
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DOI: https://doi.org/10.1007/3-540-45034-3_48
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