Part-of-Speech Tagging Using Long Short Term Memory (LSTM): Amazigh Text Written in Tifinaghe Characters

Author:

Maarouf Otman,El Ayachi Rachid

Publisher

Springer International Publishing

Reference17 articles.

1. Tan, T., Ranaivo-Malançon, B., Besacier, L., Yeong, Y., Gan, K.H., Tang, E.K.: Evaluating LSTM networks, HMM and WFST in Malay part-of-speech tagging (2017). https://www.semanticscholar.org//paper/Evaluating-LSTM-Networks%2C-HMM-and-WFST-in-Malay-Tan-Ranaivo-Malan%C3%A7on/5085ceeaa3c22b3a72b7482785251c13cd6855dc. Accessed 29 Oct 2020

2. Zen, H., Sak, H.: Unidirectional long short-term memory recurrent neural network with recurrent output layer for low-latency speech synthesis. In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4470–4474 (2015). https://doi.org/10.1109/ICASSP.2015.7178816

3. Berard, A., Pietquin, O., Servan, C., Besacier, L.: Listen and translate: a proof of concept for end-to-end speech-to-text translation. arXiv:161201744 [cs], 6 December 2016. https://arxiv.org/abs/1612.01744. Accessed 17 Jan 2021

4. Lecture Notes in Networks and Systems;A Samir,2018

5. Advances in Intelligent Systems and Computing;S Amri,2019

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