Grapheme and multilingual posterior features for under-resourced speech recognition: A study on Scottish Gaelic

@article{Rasipuram2013GraphemeAM,
  title={Grapheme and multilingual posterior features for under-resourced speech recognition: A study on Scottish Gaelic},
  author={Ramya Rasipuram and Peter Bell and Mathew Magimai-Doss},
  journal={2013 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2013},
  pages={7334-7338}
}
Standard automatic speech recognition (ASR) systems use phonemes as subword units. Thus, one of the primary resource required to build a good ASR system is a well developed phoneme pronunciation lexicon. However, under-resourced languages typically lack such lexical resources. In this paper, we investigate recently proposed grapheme-based ASR in the framework of Kullback-Leibler divergence based hidden Markov model (KL-HMM) for underresourced languages, particularly Scottish Gaelic which has no… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 10 extracted citations

Unicode-based graphemic systems for limited resource languages

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) • 2015

Cross-lingual context sharing and parameter-tying for multi-lingual speech recognition

2013 IEEE Workshop on Automatic Speech Recognition and Understanding • 2013
View 1 Excerpt

Probabilistic lexical modeling and unsupervised training for zero-resourced ASR

2013 IEEE Workshop on Automatic Speech Recognition and Understanding • 2013
View 7 Excerpts

References

Publications referenced by this paper.
Showing 1-10 of 19 references

Acoustic data-driven grapheme-to-phoneme conversion using KL-HMM

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) • 2012
View 3 Excerpts

Integrating articulatory features using Kullback-Leibler divergence based acoustic model for phoneme recognition

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) • 2011
View 1 Excerpt

Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models

2010 IEEE International Conference on Acoustics, Speech and Signal Processing • 2010

Similar Papers

Loading similar papers…