Specific language modelling for new-word detection in continuous-speech recognition

The objective of this work is to allow the INRS continuous-speech recognizer to process accurately new words and incorporate them into the vocabulary. Until now only a few new-word detectors have been reported, all of them defining an acoustic filler model different from the models used to represent vocabulary words. In this paper, we define several designs using, unlike other researchers, strictly-lexical fillers and a unique process to perform speech recognition, new-word detection and new-word phonetic transcription. Moreover, we propose here four different types of language models differing in the way they use the limited information we gathered on new words. The best combinations are found to be different from the ones we obtained for keyword spotting.