Comparing Phonetic Reduction in Russian as First and Second Language: From Psycholinguistics to Natural Language Processing

Author:

Riekhakaynen Elena I.ORCID

Publisher

Springer Singapore

Reference17 articles.

1. Mizera, P., Pollak, P.: Improving of LVCSR for Causal Czech Using Publicly Available Language Resources. In: Karpov, A., Potapova, R., Mporas, I. (eds.) Speech and Computer. SPECOM 2017. LNCS, vol. 10458, pp. 427–437. Springer, Cham (2017)

2. Ravanelli, M., Serdyuk, D. Bengio, Y.: Twin Regularization for online speech recognition. In: Proceedings of Interspeech (2018). https://arxiv.org/pdf/1804.05374.pdf . Last accessed 30 Dec 2019

3. Kipyatkova, I.: Improving Russian LVCSR using deep neural networks for acoustic and language modeling. In: Karpov, A., Jokisch, O., Potapova, R. (eds.) Speech and Computer. 20th International Conference SPECOM 2018. LNAI, vol. 11096, pp. 291–300. Springer, Cham (2018)

4. Nigmatulina, Ju, Rajeva, O., Riechakajnen, E., Slepokurova, N., Vencov, A.: How to study spoken word recognition: evidence from Russian. In: Anstatt, T., Gattnar, A. (eds.) Slavic Languages in Psycholinguistics: Chances and Challenges for Empirical and Experimental Research, Tübinger Beiträge zur Linguistik, vol. 554, pp. 175–190. Narr Francke Attempto Verlag, Tübingen (2016)

5. Johnson, K.: Massive reduction in conversational American English. In: Yoneyama, K., Maekawa, K. (eds.) Spontaneous speech: Data and analysis. Proceedings of the 1st Session of the 10th International Symposium, pp. 29–54. The National International Institute for Japanese Language, Tokyo (2004)

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