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This paper describes a new baseline system for automatic speech recognition (ASR) in the CHiME-4 challenge to promote the development of noisy ASR in speech processing communities by providing 1) state-of-the-art system with a simplified single system comparable to the complicated top systems in the challenge, 2) publicly available and reproducible recipe through the main repository in the Kaldi speech recognition toolkit.
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“Speech enhancement with LSTM recurrent neural networks and its application to noise-robust ASR, author=Weninger, Felix and Erdogan, Hakan and Watanabe, Shinji and Vincent, Emmanuel and Le Roux, Jonathan and Hershey, John R and Schuller, Björn, booktitle=International Conference on Latent Variable Analysis and Signal Separation, pages=91–99, year=2015, organization=Springer.”
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