Abstract
Robust speech recognition in noisy and reverberant conditions is an important research area in recent years. Here we present a comparative study of several spatial speech separation methods. The main performance metric is word error rate (WER) under different signal-to-noise ratio (SNR) and reverberant conditions. Extensive simulations showed that one technique known as polyaural processing stood out as the best one.
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This work was supported in part by National Science Foundation under grant IIP-0810012.
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Zhou, X., Kwan, C., Ayhan, B., Kim, C., Kumar, K., Stern, R. (2018). A Comparative Study of Spatial Speech Separation Techniques to Improve Speech Recognition. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_57
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