Interspeech'2005 - Eurospeech
Today's speech recognition systems are able to recognize arbitrary sentences over a large but finite vocabulary. However, many important speech recognition tasks feature an open, constantly changing vocabulary. (E.g. broadcast news transcription, translation of political debates, etc. Ideally, a system designed for such open vocabulary tasks would be able to recognize arbitrary, even previously unseen words. To some extent this can be achieved by using sub-lexical language models. We demonstrate that, by using a simple flat hybrid model, we can significantly improve a well-optimized state-of-the-art speech recognition system over a wide range of out-of-vocabulary rates.
Bibliographic reference. Bisani, Maximilian / Ney, Hermann (2005): "Open vocabulary speech recognition with flat hybrid models", In INTERSPEECH-2005, 725-728.