Fourth European Conference on Speech Communication and Technology

Madrid, Spain
September 18-21, 1995

Maximum Likelihood Based Discriminative Training of Acoustic Models

Albino Nogueiras-Rodriguez, José B. Marino

Universitat Politècnica de Catalunya, Barcelona, Spain

In this paper, a framework for discriminative training of acoustic models based on Generalised Probabilistic Descent (GPD) method is presented. The key feature of our proposal, Maximum Likelihood based Discriminative Training of Acoustic Models (MLDT), is the use of maximum likelihood trained HMM's instead of the original speech signal. We focus our attention in performing discriminative training applied to a discrete hidden Markov models continuos speech recogniser, achieving a 4.6% error rate reduction on a Spanish speaker-independent phoneme recognition task.

Full Paper

Bibliographic reference.  Nogueiras-Rodriguez, Albino / Marino, José B. (1995): "Maximum likelihood based discriminative training of acoustic models", In EUROSPEECH-1995, 85-88.