Name
Abstract | ||
|---|---|---|
This paper briefly reviews state of the art related to the topic of speech variability sources in automatic speech recognition systems. It focuses on some variations within the speech signal that make the ASR task difficult. The variations detailed in the paper are intrinsic to the speech and affect the different levels of the ASR processing chain. For different sources of speech variation, the paper summa- rizes the current knowledge and highlights specific feature extraction or modeling weaknesses and current trends. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1661452 | Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference |
Keywords | Field | DocType |
feature extraction,speech processing,speech recognition,automatic speech recognition,feature extraction,intrinsic speech variation,speech signal,speech variability sources | Speech corpus,Speech processing,Speech coding,Audio mining,Voice activity detection,Computer science,Speech recognition,Natural language processing,Artificial intelligence,Speech technology,Intelligibility (communication),Acoustic model | Conference |
Volume | ISSN | ISBN |
5 | 1520-6149 | 1-4244-0469-X |
Citations | PageRank | References |
3 | 0.39 | 37 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benzeguiba, M. | 1 | 3 | 0.39 |
| Renato De Mori | 2 | 960 | 161.75 |
| O. Deroo | 3 | 139 | 7.15 |
| Dupont, S. | 4 | 3 | 0.39 |