Vocabulary Expansion for the Sub-word WFST-Based Automatic Speech Recognition System
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-18344-7_41
Reference41 articles.
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2. Smit, P., Virpioja, S., Kurimo, M., et al.: Improved subword modeling for WFST-based speech recognition. In: Interspeech, pp. 2551–2555 (2017)
3. Wang, S., Li, G.: Overview of end-to-end speech recognition. J. Phys: Conf. Ser. 1187(5), 052068 (2019). https://doi.org/10.1088/1742-6596/1187/5/052068
4. Rao, K., Sak, H., Prabhavalkar, R.: Exploring architectures, data and units for streaming end-to-end speech recognition with RNN-transducer. 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp. 193–199. IEEE (2017)
5. Chiu, Ch.-Ch., et al.: State-of-the-art speech recognition with sequence-to-sequence models. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4774–4778. IEEE (2018)
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