Pronunciation modeling by sharing gaussian densities across phonetic models

@article{Saralar1999PronunciationMB,
  title={Pronunciation modeling by sharing gaussian densities across phonetic models},
  author={M. Saraçlar and H. Nock and S. Khudanpur},
  journal={Comput. Speech Lang.},
  year={1999},
  volume={14},
  pages={137-160}
}
Conversational speech exhibits considerable pronunciation variability, which has been shown to have a detrimental effect on the accuracy of automatic speech recognition. There have been many attempts to model pronunciation variation, including the use of decision trees to generate alternate word pronunciations from phonemic baseforms. Use of pronunciation models during recognition is known to improve accuracy. This paper describes the incorporation of pronunciation models into acoustic model… Expand
Pronunciation ambiguity vs. pronunciation variability in speech recognition
  • M. Saraçlar, S. Khudanpur
  • Computer Science
  • 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100)
  • 2000
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