Name
Title | ||
|---|---|---|
Speech Recognition In Mixed Sound Of Speech And Music Based On Vector Quantization And Non-Negative Matrix Factorization |
Abstract | ||
|---|---|---|
This paper describes a speech recognition method for mixed sound, consisting of speech and music, that removes the music only based on vector quantization (VQ) and non-negative matrix factorization (NMF). For isolated word recognition using the clean speech model, an improvement of about 15% was obtained compared with the case of not removing music. Furthermore, a high recognition rate of about 90% was achieved, even under the 0 dB condition using a model trained from the mixed sound after removing the music according to the VQ method. |
Year | Venue | Keywords |
|---|---|---|
2011 | 12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | speech recognition, mixed sound, music removal, vector quantization, non-negative matrix factorization |
Field | DocType | Citations |
Pattern recognition,Computer science,Word recognition,Matrix decomposition,Speech recognition,Vector quantization,Non-negative matrix factorization,Artificial intelligence,Speech model | Conference | 2 |
PageRank | References | Authors |
0.42 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shoichi Nakano | 1 | 3 | 1.13 |
| Kazumasa Yamamoto | 2 | 141 | 15.26 |
| Seiichi Nakagawa | 3 | 598 | 104.03 |