9th Annual Conference of the International Speech Communication Association

Brisbane, Australia
September 22-26, 2008

Discrimininative Training of Narrow Band - Wide Band Adapted Systems for Meeting Recognition

Martin Karafiát (1), Lukáš Burget (1), Thomas Hain (2), Jan Černocký (1)

(1) Brno University of Technology, Czech Republic; (2) University of Sheffield, UK

The amount of training data has a crucial effect on the accuracy of HMM based meeting recognition systems. One of the largest collections of speech data is conversational telephone speech which was found to match speech in meetings well. However it is naturally recorded with limited bandwidth. In previous work we presented a scheme that allows to transform wide-band meeting data into the same space for improved model training. In this paper we focused on integration of discriminative adaptation into this scheme. This integration is not straightforward and we present the complexity of this process. The models are tested on the NIST RT'05 meeting evaluation where a relative reduction in word error rate of 5.6% against non-adapted meeting system was achieved.

Full Paper

Bibliographic reference.  Karafiát, Martin / Burget, Lukáš / Hain, Thomas / Černocký, Jan (2008): "Discrimininative training of narrow band - wide band adapted systems for meeting recognition", In INTERSPEECH-2008, 1217-1220.