Robust speech recognition over mobile networks using combined weighted viterbi decoding and subvector based error concealment

Abstract

Robustness against transmission errors is one of the primary barriers to the widespread application of automatic speech recognition (ASR) in mobile communications. We have previously proposed a subvector based error concealment (EC) method that conducts error detection and mitigation in the feature-domain at the subvector level. This paper presents a weighted Viterbi decoding (WVD) algorithm that works in the model domain for counteracting unreliable features generated by the subvector based EC. The reliability of each feature is estimated during the process of subvector based EC and is used by the WVD for modifying the observation probability of the feature. Recognition experiments are conducted on the Aurora 2 database corrupted by GSM error pattern EP3. Combining the WVD and the subvector EC achieves 70% and 24% performance improvement as compared to the ETSI-DSR standard and the subvector based EC, respectively. Index Terms: distributed speech recognition, error concealment, split vector quantization, weighted Viterbi