Name
Abstract | ||
|---|---|---|
We present a two stage automatic speech recognition architecture suited for applications, such as spoken document retrieval, where large scale language models can be used and very low out-of-vocabulary rates need to be reached. The proposed system couples a weakly constrained phone-recognizer with a phone-to-word decoder that was originally developed for phrase-based statistical machine translation. The decoder permits to efficiently decode confusion networks in input, and to exploit large scale unpruned language models. Preliminary experiments are reported on the transcription of speeches of the Italian parliament. The use of phone confusion networks as interface between the two decoding steps permits to reduce the WER by 28%, thus making the system perform relatively close to a state-of-the-art baseline using a comparable language model. |
Year | Venue | Keywords |
|---|---|---|
2008 | INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5 | Automatic speech recognition, decoding algorithm |
Field | DocType | Citations |
Architecture,Computer science,Machine translation,Phrase,Speech recognition,Exploit,Phone,Document retrieval,Decoding methods,Language model | Conference | 3 |
PageRank | References | Authors |
0.82 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| nicola bertoldi | 1 | 1777 | 95.10 |
| marcello federico | 2 | 2420 | 179.56 |
| Daniele Falavigna | 3 | 572 | 88.38 |
| Matteo Gerosa | 4 | 172 | 13.14 |