| Paper: | SP-L6.3 | ||
| Session: | Feature Analysis for Speech Recognition | ||
| Time: | Thursday, May 20, 13:40 - 14:00 | ||
| Presentation: | Lecture | ||
| Topic: | Speech Processing: Feature Extraction | ||
| Title: | THE ETSI EXTENDED DISTRIBUTED SPEECH RECOGNITION (DSR) STANDARDS: CLIENT SIDE PROCESSING AND TONAL LANGUAGE RECOGNITION EVALUATION | ||
| Authors: | Alexander Sorin; IBM Labs | ||
| Tenkasi Ramabadran; Motorola Labs | |||
| Dan Chazan; IBM Labs | |||
| Ron Hoory; IBM Labs | |||
| Michael McLaughlin; Motorola Labs | |||
| David Pearce; Motorola Labs | |||
| Fan Wang; IBM Labs | |||
| Yaxin Zhang; Motorola Labs | |||
| Abstract: | In this paper we present work that has been carried out in developing the ETSI Extended DSR standards ES 202 211 and ES 202 212 [1][2]. These standards extend the previous ETSI DSR standards: basic front-end ES 201 108 and advanced (noise robust) front-end ES 202 050 respectively. The extensions enable enhanced tonal language recognition as well as server-side speech reconstruction capability. This paper discusses the client-side estimation of pitch and voicing class parameters whereas a companion paper discusses the server-side speech reconstruction. Experimental results show enhancement of tonal language recognition rates of proprietary recognition engines, when the standard extensions are used. | ||
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