Ninth International Conference on Spoken Language Processing

Pittsburgh, PA, USA
September 17-21, 2006

Discriminative Models for Spoken Language Understanding

Ye-Yi Wang, Alex Acero

Microsoft Research, USA

This paper studies several discriminative models for spoken language understanding (SLU). While all of them fall into the conditional model framework, different optimization criteria lead to conditional random fields, perceptron, minimum classification error and large margin models. The paper discusses the relationship amongst these models and compares them in terms of accuracy, training speed and robustness.

Full Paper

Bibliographic reference.  Wang, Ye-Yi / Acero, Alex (2006): "Discriminative models for spoken language understanding", In INTERSPEECH-2006, paper 1766-Thu2A1O.6.