Name
Title | ||
|---|---|---|
Modulation Filter Learning Using Deep Variational Networks for Robust Speech Recognition |
Abstract | ||
|---|---|---|
The performance of a typical speech recognition system is degraded in the presence of extrinsic sources like noise and due to the recording artifacts like reverberation. The principle of modulation filtering attempts to remove the spectro-temporal modulations of the speech signal that are more susceptible to noise while preserving the key modulations for speech recognition. While traditional appro... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JSTSP.2019.2913965 | IEEE Journal of Selected Topics in Signal Processing |
Keywords | Field | DocType |
Modulation,Speech recognition,Decoding,Spectrogram,Reverberation,Convolution,Training | Reverberation,Autoencoder,Spectrogram,Computer science,Communication channel,Filter (signal processing),Speech recognition,Modulation,Baseline system,Modulation (music) | Journal |
Volume | Issue | ISSN |
13 | 2 | 1932-4553 |
Citations | PageRank | References |
2 | 0.35 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Purvi Agrawal | 1 | 2 | 2.38 |
| Sriram Ganapathy | 2 | 252 | 39.62 |