Name
Abstract | ||
|---|---|---|
In recent years, data from various auxiliary acoustic and nonacoustic sensors have been used for enhancing noisy speech. These include bone-conduction microphones, surface electromyographic sensors, ultrasonic imaging of facial movements, etc. The signal from such sensors is correlated with the speech signal to varying degrees, and unlike microphone data, is typically not affected by acoustic background noise, making its use attractive for speech enhancement. In this paper, we discuss the measurement of the utility of such data from an information-theoretic perspective, and quantify the information that is shared between clean speech and the auxiliary signal, which is not present in the observed noisy speech signal. The measure is applied to simultaneously recorded air-and bone-conducted speech data. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6639079 | ICASSP |
Keywords | Field | DocType |
speech enhancement,microphone data,ultrasonic imaging,auxiliary signal,auxiliary acoustic sensors,microphones,surface electromyographic sensors,nonacoustic sensors,bone-conduction microphones,air-and-bone-conducted speech data,sensors,auxiliary sensor data utility,mutual information,bone conduction,noisy speech,information-theoretic perspective,noisy speech signal,noise measurement,speech,signal to noise ratio,acoustics | Speech enhancement,Speech processing,Background noise,Computer science,Speech recognition,Ultrasonic imaging,Microphone | Conference |
ISSN | Citations | PageRank |
1520-6149 | 1 | 0.36 |
References | Authors | |
5 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sriram Srinivasan | 1 | 379 | 27.92 |
| Patrick Kechichian | 2 | 6 | 1.91 |