| Paper: | SP-L3.1 | ||
| Session: | Distributed Speech Recognition | ||
| Time: | Wednesday, May 19, 13:00 - 13:20 | ||
| Presentation: | Lecture | ||
| Topic: | Speech Processing: Robust Speech Recognition | ||
| Title: | SOFT DECODING STRATEGIES FOR DISTRIBUTED SPEECH RECOGNITION OVER IP NETWORKS | ||
| Authors: | Antonio Cardenal-López; University of Vigo | ||
| Laura Docío-Fernández; University of Vigo | |||
| Carmen García-Mateo; University of Vigo | |||
| Abstract: | In Distributed Speech Recognition, speech feature vectors are obtained at the client side, and transmitted to the remote server for recognition. In this paper, we investigate the robustness of the remote recognizer against the inherent packet loss in an Internet communication. In the decoding process, we propose to apply techniques used for ``missing data'' problems. The idea is to use a simple approach of error concealment to recover the non-received speech frames, and then to consider these recovered speech frames as not completely reliable. Thus, at recognition stage, our recognition engine uses a weighted (or soft decision) Viterbi algorithm in order to take into account the reliability of the recovered speech frames. Results on Aurora databases show that the proposed approach provides good recognition performance over a wide range of network conditions. | ||
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