Name
Abstract | ||
|---|---|---|
This paper presents a new approach to spoken document information retrieval for spontaneous speech corpora. The classical approach to this problem is the use of an automatic speech recognizer (ASR) combined with standard information retrieval techniques. However, ASRs tend to produce transcripts of spontaneous speech with significant word error rate, which is a drawback for standard retrieval techniques. To overcome such a limitation, our method is based on an approximated sequence alignment algorithm to search "sounds like" sequences. Our approach does not depend on extra information from the ASR and outperforms up to 7 points the precision of state-of-the-art techniques in our experiments. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-87391-4_37 | TSD |
Keywords | Field | DocType |
spoken document retrieval,spontaneous speech corpus,extra information,approximated sequence alignment algorithm,approximated sequence alignment,document information retrieval,spontaneous speech,new approach,standard information retrieval technique,standard retrieval technique,classical approach,automatic speech recognizer,sequence alignment,information retrieval,word error rate | Sequence alignment,Automatic speech,Speech analytics,Computer science,Word error rate,Speech recognition,Artificial intelligence,Natural language processing,Document retrieval,Visual Word | Conference |
Volume | ISSN | Citations |
5246 | 0302-9743 | 4 |
PageRank | References | Authors |
0.43 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pere Comas | 1 | 82 | 7.23 |
| Jordi Turmo | 2 | 306 | 30.52 |
| jorge turmo borras | 3 | 6 | 1.48 |