ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

Efficient mixed-order hidden Markov model inference

Ludwig Schwardt, Johan du Preez

Recent studies have shown that high-order hidden Markov models (HMMs) are feasible and useful for spoken language processing. This paper extends the fixed-order versions to ergodic mixedorder HMMs, which allow the modelling of variable-length contexts with significantly less parameters. A novel training procedure automatically infers the number of states and the topology of the HMM from the training set, based on information-theoretic criteria. This is done by incorporating only high-order contexts with sufficient support in the data. The mixed-order training algorithm is faster than fixed-order methods, with similar classifi- cation performance in language identification tasks.


Cite as: Schwardt, L., Preez, J.d. (2000) Efficient mixed-order hidden Markov model inference. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 2, 238-241

@inproceedings{schwardt00_icslp,
  author={Ludwig Schwardt and Johan du Preez},
  title={{Efficient mixed-order hidden Markov model inference}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 2, 238-241}
}