| Paper: | SP-P16.11 | ||
| Session: | Speech Modeling for Robust Speech Recognition | ||
| Time: | Friday, May 21, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Speech Processing: Robust Speech Recognition | ||
| Title: | AUTOMATIC RECOGNITION OF BLUETOOTH SPEECH IN 802.11 INTERFERENCE AND THE EFFECTIVENESS OF INSERTION-BASED COMPENSATION TECHNIQUES | ||
| Authors: | Amr Nour-Eldin; Université du Québec | ||
| Douglas O'Shaughnessy; Université du Québec | |||
| Hesham Tolba; Université du Québec | |||
| Abstract: | In this paper, we investigate the ASR performance of speech transmitted over a noisy Bluetooth RF channel. Bluetooth shares its transmission channel with IEEE 802.11-based devices. Despite Bluetooth's frequency hopping scheme, our investigation shows that Bluetooth packet loss rates may reach up to 38% in unfavorable 802.11 interference conditions, and as Bluetooth uses a CVSD codec with syllabic companding, these packet losses not only manifest themselves as segments of missing speech upon CVSD decoding, but also as incorrect scaling of subsequent successfully received voice packets as CVSD step-size information is also lost. We investigate the effects of these degradations on the ASR performance of Bluetooth speech, and accordingly propose alternative CVSD decoder schemes employing insertion-based techniques for compensating for these effects. Results show that our proposed techniques improve ASR performance considerably while requiring only minor modifications to the current Bluetooth receiver. | ||
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