ISCA Archive Interspeech 2013
ISCA Archive Interspeech 2013

Experiments towards a better LVCSR system for tamil

Melvin Jose Johnson Premkumar, Ngoc Thang Vu, Tanja Schultz

This paper summarizes our latest efforts in the development of a Large Vocabulary Continuous Speech Recognition (LVCSR) system for Tamil at different levels: pronunciation dictionary, language modeling (LM) and front-end. Usually in Tamil there are not many word-pronunciation pairs to train data-driven grapheme-to-phoneme (G2P) converters. Therefore, we explore the correlation between the amount of training data and the performance of the grapheme-to-phoneme (G2P) conversion. To address the morphological complexity of Tamil, we investigate different levels of morphemes for language modeling including a comparison between our Dictionary Unit Merging Algorithm (DUMA) and Morfessor, followed by various experiments on hybrid systems using word and morpheme LMs. Finally, we integrate our multilingual bottle-neck features framework with Tamil LVCSR. The final best system produced 21.34% Syllable Error Rate (SyllER) on our Tamil test set.


doi: 10.21437/Interspeech.2013-519

Cite as: Premkumar, M.J.J., Vu, N.T., Schultz, T. (2013) Experiments towards a better LVCSR system for tamil. Proc. Interspeech 2013, 2202-2206, doi: 10.21437/Interspeech.2013-519

@inproceedings{premkumar13_interspeech,
  author={Melvin Jose Johnson Premkumar and Ngoc Thang Vu and Tanja Schultz},
  title={{Experiments towards a better LVCSR system for tamil}},
  year=2013,
  booktitle={Proc. Interspeech 2013},
  pages={2202--2206},
  doi={10.21437/Interspeech.2013-519}
}