ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

Hybrid SVM/HMM architectures for speech recognition

Aravind Ganapathiraju, Jonathan Hamaker, Joseph Picone

In this paper, we describe the use of a powerful machine learning scheme, Support Vector Machines (SVM), within the framework of hidden Markov model (HMM) based speech recognition. The hybrid SVM/HMM system has been developed based on our public domain toolkit. The hybrid system has been evaluated on the OGI Alphadigits corpus and performs at 11.6% WER, as compared to 12.7% with a triphone mixture-Gaussian HMM system, while using only a fifth of the training data used by triphone system. Several important issues that arise out of the nature of SVM classifiers have been addressed. We are in the process of migrating this technology to large vocabulary recognition tasks like SWITCHBOARD.


Cite as: Ganapathiraju, A., Hamaker, J., Picone, J. (2000) Hybrid SVM/HMM architectures for speech recognition. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 4, 504-507

@inproceedings{ganapathiraju00b_icslp,
  author={Aravind Ganapathiraju and Jonathan Hamaker and Joseph Picone},
  title={{Hybrid SVM/HMM architectures for speech recognition}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 4, 504-507}
}