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A Study of Phoneme and Grapheme Based Context-Dependent ASR Systems
Machine Learning for Multimodal Interaction
In this paper we present a study of automatic speech recognition systems using context-dependent phonemes and graphemes as sub-word units based on the conventional HMM/GMM system as well as tandem system. Experimental studies conducted on three different continuous speech recognition tasks show that systems using only context-dependent graphemes can yield competitive performance on small to medium vocabulary tasks when compared to a context-dependent phoneme-based automatic speech recognitiondoi:10.1007/978-3-540-78155-4_19 dblp:conf/mlmi/DinesM07 fatcat:mccxqgpro5godfcoucrtmwzz2i