Name
Title | ||
|---|---|---|
Role play dialogue topic model for language model adaptation in multi-party conversation speech recognition |
Abstract | ||
|---|---|---|
This paper introduces an unsupervised language model adaptation technique for multi-party conversation speech recognition. The use of topic models provides one of the most accurate frameworks for unsupervised language model adaptation since they can inject long-range topic information into language models. However, conventional topic models are not suitable for multi-party conversation because they assume that each speech set has each different topic. In a multi-party conversation, each speaker will share the same conversation topic and each speaker utterance will depend on both topic and speaker role. Accordingly, this paper proposes new concept of the “role play dialogue topic model” to utilize multiparty conversation attributes. The proposed topic model can share the topic distribution among each speaker and can also consider both topic and speaker role. The proposed topic model based adaptation realizes a new framework that sets multiple recognition hypotheses for each speaker and simultaneously adapts a language model for each speaker role. We use a call center dialogue data set in speech recognition experiments to show the effectiveness of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICASSP.2014.6854528 | Acoustics, Speech and Signal Processing |
Keywords | Field | DocType |
natural language processing,speech recognition,unsupervised learning,call center dialogue data set,long-range topic information,multiparty conversation speech recognition,multiple recognition hypotheses,role play dialogue topic model,speaker role,speaker utterance,speech set,topic distribution,unsupervised language model adaptation technique,Unsupervised language model adaptation,multi-party conversation speech recognition,topic model | Conversation,Computer science,Utterance,Speech recognition,Speaker recognition,Artificial intelligence,Natural language processing,Speaker diarisation,Topic model,Language model | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
15 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryo Masumura | 1 | 25 | 28.24 |
| Takanobu Oba | 2 | 53 | 12.09 |
| Hirokazu Masataki | 3 | 18 | 9.21 |
| Osamu Yoshioka | 4 | 29 | 5.66 |