Name
Title | ||
|---|---|---|
Single channel dereverberation method in log-melspectral domain using limited stereo data for distant speaker identification. |
Abstract | ||
|---|---|---|
In this paper, we present a feature enhancement method that uses neural networks (NNs) to map the reverberant feature in a log-melspectral domain to its corresponding anechoic feature. The mapping is done by cascade NNs trained using Cascade2 algorithm with an implementation of segment-based normalization. We assumed that the dimensions of feature were independent from each other and experimented on several assumptions of the room transfer function for each dimension. Speaker identification system was used to evaluate the method. Using limited stereo data, we could improve the identification rate for simulated and real datasets. On the simulated dataset, we could show that the proposed method is effective for both noiseless and noisy reverberant environments, with various noise and reverberation characteristics. On the real dataset, we could show that by using 6 independent NNs configuration for 24-dimensional feature and only 1 pair of utterances we could get 35% average error reduction relative to the baseline, which employed cepstral mean normalization (CMN). |
Year | Venue | Keywords |
|---|---|---|
2013 | Asia-Pacific Signal and Information Processing Association Annual Summit and Conference | feature extraction,neural nets,speaker recognition,reverberation,transfer functions |
Field | DocType | ISSN |
Reverberation,Normalization (statistics),Pattern recognition,Computer science,Speech recognition,Feature extraction,Anechoic chamber,Transfer function,Speaker recognition,Artificial intelligence,Cascade,Artificial neural network | Conference | 2309-9402 |
Citations | PageRank | References |
1 | 0.35 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aditya Arie Nugraha | 1 | 104 | 7.91 |
| Kazumasa Yamamoto | 2 | 33 | 7.58 |
| Seiichi Nakagawa | 3 | 598 | 104.03 |