Name
Title | ||
|---|---|---|
Accent modeling based on pronunciation dictionary adaptation for large vocabulary Mandarin speech recognition |
Abstract | ||
|---|---|---|
A method of accent modeling through Pronunciation Dictionary Adaptation (PDA) is presented. We derive the pronunciation variation between canonical speaker groups and accent groups and add an encoding of the differences to a canonical dictionary to create a new, adapted dictionary that reflects the accent characteristics. The pronunciation variation information is then integrated with acoustic and language models into a one-pass search framework. It is assumed that acoustic deviation and pronunciation variation are independent but complementary phenomena that cause poor performance among accented speakers. Therefore, MLLR, an efficient model adaptation technique, is also presented both alone and in combination with PDA. It is shown that when PDA, MLLR and PDA+MLLR are used, error rate reductions of 13.9%, 24.1% and 28.4% respectively are achieved. |
Year | Venue | Keywords |
|---|---|---|
2000 | INTERSPEECH | language model,speech recognition,error rate |
Field | DocType | Citations |
Pronunciation,Computer science,Word error rate,Speech recognition,Natural language processing,Artificial intelligence,Vocabulary,Language model,Mandarin speech recognition,Encoding (memory) | Conference | 17 |
PageRank | References | Authors |
1.77 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Huang | 1 | 218 | 23.06 |
| Eric Chang | 2 | 625 | 49.79 |
| Jian-Lai Zhou | 3 | 184 | 20.85 |
| Kai-fu Lee | 4 | 795 | 247.70 |