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NTIS 바로가기한국음향학회지= The journal of the acoustical society of Korea, v.41 no.3, 2022년, pp.335 - 341
이채원 (한양대학교 융합전자공학과) , 장준혁 (한양대학교 융합전자공학과)
In this paper, we adopt a transformer that shows remarkable performance in natural language processing as an acoustic model of hybrid speech recognition. The transformer acoustic model uses attention structures to process sequential data and shows high performance with low computational cost. This p...
B. Juang and L. Rabiner, "Hidden Markov models for speech recognition," Technometrics, 33, 251-272 (1991).
A. Senior, H. Sak, and I. Shafran, "Context dependent phone models for LSTM RNN acoustic modelling," Proc. IEEE ICASSP, 4585-4589 (2015).
J. Li, V. Lavrukhin, B. Ginsburg, and R. Leary, "Jasper: An end-to-end convolutional neural acoustic model," arXiv preprint arXiv:1904.03288 (2019).
K. Chen and Q. Huo, "Training deep bidirectional LSTM acoustic model for LVCSR by a context-sensitive-chunk BPTT approach," IEEE/ACM Transactions on Audio, Speech, and Language Processing, 24 (2016).
L. Bahl, P. Brown, P. Souza, and R. Mercer, "Maximum mutual information estimation of hidden Markov model parameters for speech recognition," Proc. ICASSP, 49-52 (1986).
D. Povey, D. Kanevsky, B. Kingsbury, B. Ranabhadran, G. Saon, and K. Visweswariah, "Boosted MMI for model and feature-space discriminative training," Proc. IEEE ICASSP, 4057-4060 (2008).
M. Gibson and T. Hain, "Hypothesis spaces for minimum Bayes risk training in large vocabulary speech recognition," Proc. Interspeech, 2406-2409 (2006).
D. Povey, V. Peddinti, D. Galvez, P. Ghahremani, and V. Manohar, "Purely sequence-trained neural networks for ASR based on lattice-free MMI," Proc. Interspeech, 2751-2755 (2016).
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. Gomez, L. Kaiser, and I. Polosukhin, "Attention is all you need," Advances in neural information processing systems, 30 (2017).
K. Vesely, A. Ghoshal, L. Burget, and D. Povey, "Sequence-discriminative training of deep neural networks," Proc. Interspeech, 2345-2349 (2013).
Y. Wang, A. mohamed, D. Le, C. Liu, and A. Xiao, "Transformer-based acoustic modeling for hybrid speech recognition," Proc. IEEE ICASSP, 6874-6878 (2020).
V. Panayotov, G. Chen, D. Povey, and S.Khudanpur, "Librispeech: an asr corpus based on public domain audio books," Proc. IEEE ICASSP, 5206-5210 (2015).
S. Watanabe, T. Hori, S. karita, and T. Hayashi, "Espnet: End-to-end speech processing toolkit," arXiv preprint arXiv:1804.00015 (2018).
D. Povey, A. Ghoshal, G. Boulianne, L. Burget, O. Glembek, N. Goel, M. Hannemann, P. Motlicek, Y. Qian, P. Schwarz, J. Silovsky, G. Stemmer, and K. Vesely, "The Kaldi speech recognition toolkit," Proc. ASRU, (2011).
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, and Z. Vito, "Pytorch: An imperative style, high-performance deep learning library," Advances in neural information processing systems, 32 (2019).
L. Lu, X. Xiao, Z. Chen, and Y. Gong, "Pykaldi2: Yet another speech toolkit based on kaldi and pytorch," arXiv preprint arXiv:1907.05955 (2019).
Y. Shao and Y. Wang, "Pychain: A fully parallelized pytorch implementation of lf-mmi for end-to-end asr," arXiv preprint arXiv:2005.09824 (2020).
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