Name
Title | ||
|---|---|---|
Efficient data selection for speech recognition based on prior confidence estimation using speech and monophone models |
Abstract | ||
|---|---|---|
This paper proposes an efficient speech data selection technique that can identify those data that will be well recognized. Conventional confidence measure techniques can also identify well-recognized speech data. However, those techniques require a lot of computation time for speech recognition processing to estimate confidence scores. Speech data with low confidence should not go through the time-consuming recognition process since they will yield erroneous spoken documents that will eventually be rejected. The proposed technique can select the speech data that will be acceptable for speech recognition applications. It rapidly selects speech data with high prior confidence based on acoustic likelihood values and using only speech and monophone models. Experiments show that the proposed confidence estimation technique is over 50 times faster than the conventional posterior confidence measure while providing equivalent data selection performance for speech recognition and spoken document retrieval. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.csl.2014.05.001 | Computer Speech and Language |
Keywords | Field | DocType |
gaussian mixture model,68t10,speech recognition,context independent model,data selection,spoken document retrieval,43.72.ne | Low Confidence,Data selection,Audio mining,Computer science,Voice activity detection,Speech recognition,Artificial intelligence,Natural language processing,Document retrieval,Mixture model,Computation,Acoustic model | Journal |
Volume | Issue | ISSN |
28 | 6 | 0885-2308 |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Satoshi Kobashikawa | 1 | 28 | 9.73 |
| Taichi Asami | 2 | 22 | 10.49 |
| Yoshikazu Yamaguchi | 3 | 77 | 11.18 |
| Hirokazu Masataki | 4 | 18 | 9.21 |
| Satoshi Takahashi | 5 | 0 | 0.34 |