In this paper we describe a novel discriminative method for pruning pronunciation dictionary. The algorithm removes those entries from the dictionary that affect negatively on speech recognition word error rate. The implementation is simple and requires no tunable parameters. We have carried out preliminary speech recognition experiments, pruning multiword pronunciations created by a phonetician. With the task in hand, we achieved only minimal improvements in recognition results. We are optimistic that the algorithm will prove to be useful in pruning larger dictionaries containing automatically generated pronunciations.
|Title of host publication||7th Conference on Speech Technology and Human-Computer Dialogue, (SpeD 2013), Cluj-Napoca, 16 Oct 2013 - 19 Oct 2013|
|Publication status||Published - 2013|
|MoE publication type||A4 Article in a conference publication|
- speech recognition
- pronunciation modeling
- discriminative learning
- dictionary pruning