Name
Abstract | ||
|---|---|---|
The detection and characterization, in audiovisual documents, of speech utterances where person names are pronounced, is an important cue for spoken content analysis. This paper tackles the problematic of retrieving spoken person names in the 1-Best ASR outputs of broadcast TV shows. Our assumption is that a person name is a latent variable produced by the lexical context it appears in. Thereby, a spoken name could be derived from ASR outputs even if it has not been proposed by the speech recognition system. A new context modelling is proposed in order to capture lexical and structural information surrounding a spoken name. The fundamental hypothesis of this study has been validated on broadcast TV documents available in the context of the REPERE challenge. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6639318 | 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
spoken document retrieval, spoken name detection, lexical context representation | Broadcasting,Content analysis,Computer science,Speech recognition,Latent variable,Natural language processing,Artificial intelligence,Document handling,Context modelling,Broadcast television systems | Conference |
ISSN | Citations | PageRank |
1520-6149 | 8 | 0.55 |
References | Authors | |
15 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Bigot | 1 | 45 | 5.39 |
| Grégory Senay | 2 | 57 | 7.02 |
| georges linar es | 3 | 136 | 29.55 |
| corinne fredouille | 4 | 537 | 44.53 |
| richard dufour | 5 | 98 | 23.98 |