De Silva, L.C., Morikawa, C. and Petra, I.M., 2012. State of the art of smart homes. Engineering Applications of Artificial Intelligence, 25(7), pp.1313-1321.
 Picone, J., 1996. Fundamentals of speech recognition: A short course. Institute for Signal and Information Processing, Mississippi State University.
 Giannakopoulos, T., Tatlas, N.A., Ganchev, T. and Potamitis, I., 2005. A practical, real-time speech-driven home automation front-end.
IEEE Transactions on Consumer Electronics, 51(2), pp.514-523.
 McLoughlin, I.V. and Sharifzadeh, H.R., 2007, December. Speech recognition engine adaptions for smart home dialogues. In Information, Communications & Signal Processing, 2007 6th International Conference on (pp. 1-5). IEEE.
 Graves, A., Mohamed, A.R. and Hinton, G., 2013, May. Speech recognition with deep recurrent neural networks. In Acoustics, speech and signal processing (icassp), 2013 ieee international conference on (pp. 6645-6649). IEEE.
 Graves, A., 2012. Sequence transduction with recurrent neural networks. arXiv preprint arXiv:1211.3711.
 Vinyals, O., Ravuri, S.V. and Povey, D., 2012, March. Revisiting recurrent neural networks for robust ASR. In Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on (pp. 4085-4088). IEEE.
 Li, J., Zhang, H., Cai, X. and Xu, B., 2015. Towards end-to-end speech recognition for chinese mandarin using long short-term memory recurrent neural networks. In Sixteenth annual conference of the international speech communication association.
 Schuster, M. and Paliwal, K.K., 1997. Bidirectional recurrent neural networks. IEEE Transactions on Signal Processing, 45(11), pp.2673-2681.
 Graves, A., 2013. Generating sequences with recurrent neural networks. arXiv preprint arXiv:1308.0850.
 Hochreiter, S. and Schmidhuber, J., 1997. Long short-term memory. Neural computation, 9(8), pp.1735-1780.
 Graves, A., Fernández, S., Gomez, F. and Schmidhuber, J., 2006, June. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In Proceedings of the 23rd international conference on Machine learning (pp. 369-376). ACM.
 Hwang, K., Lee, M. and Sung, W., 2015. Online keyword spotting with a character-level recurrent neural network. arXiv preprint arXiv:1512.08903.
 Graves, A. and Jaitly, N., 2014, January. Towards end-to-end speech recognition with recurrent neural networks. In International Conference on Machine Learning (pp. 1764-1772).
 Povey, D., Ghoshal, A., Boulianne, G., Burget, L., Glembek, O., Goel, N., Hannemann, M., Motlicek, P., Qian, Y., Schwarz, P. and Silovsky, J., 2011. The Kaldi speech recognition toolkit. In IEEE 2011 workshop on automatic speech recognition and understanding (No. EPFL-CONF-192584). IEEE Signal Processing Society.
 Parr, T., 2013. The definitive ANTLR 4 reference. Pragmatic Bookshelf.
 Panayotov, V., Chen, G., Povey, D. and Khudanpur, S., 2015, April. Librispeech: an ASR corpus based on public domain audio books. In Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on (pp. 5206-5210). IEEE.
 Warden, P., 2018. Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition. arXiv preprint arXiv:1804.03209.