Audiovisual Speech Separation Based on Independent Vector Analysis Using a Visual Voice Activity Detector
| Autor: | Pierre Narvor, Christian Jutten, Bertrand Rivet |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Voice activity detection
Underdetermined system Computer science Speech recognition Detector Binary number 020206 networking & telecommunications Context (language use) 02 engineering and technology Blind signal separation 030507 speech-language pathology & audiology 03 medical and health sciences Identification (information) Rate of convergence 0202 electrical engineering electronic engineering information engineering 0305 other medical science |
| Zdroj: | Latent Variable Analysis and Signal Separation ISBN: 9783319535463 LVA/ICA |
| DOI: | 10.1007/978-3-319-53547-0_24 |
| Popis: | In this paper, we present a way of improving the Independent Vector Analysis in the context of blind separation of convolutive mixtures of speech signals. The periods of activity and inactivity of one or more speech signals are first detected using a binary visual voice activity detector based on lip movements and then fed into a modified Independent Vector Analysis algorithm to achieve the separation. Presented results show that this approach improves separation and identification of sources in a determined case with a higher convergence rate, and is also able to enhance a specific source in an underdetermined mixture. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|