[1] فائزه بنیاردلان، احمد اکبری، بابک ناصرشریف، «حذف نویز و استخراج ویژگیهای گلوگاه در سطح زیرباند توسط شبکههای خودرمزگذار عمیق برای بازشناسی گفتار»، کنفرانس پردازش سیگنال و سیستمهای هوشمند، دانشگاه صنعتی امیرکبیر، دوره اول، 1394.
[2] مجتبی غلامیپور، بابک ناصرشریف، «مقاومسازی ویژگیهای مل کپستروم نسبت به نویز با استفاده از شبکه باور عمیق»، کنفرانس پردازش سیگنال و سیستمهای هوشمند، دانشگاه صنعتی امیرکبیر، دوره اول، 1394.
[3] مجتبی حاجی آبادی، عباس ابراهیمی مقدم، حسین خوش بین، «حذف نویز صوتی مبتنی بر یک الگوریتم وفقی نوین»، مجله مهندسی برق دانشگاه تبریز، دوره 46، شماره 3، ص: 139-147، پائیز 1395.
[4] مسعود گراوانچیزاده، ساناز قائمی سردرودی، «بهبود کیفیت گفتار مبتنی بر بهینهسازی ازدحام ذرات با استفاده از ویژگیهای ماسکگذاری سیستم شنوائی انسان»، مجله مهندسی برق دانشگاه تبریز، دوره 46، شماره 3، ص: 287-297، پاییز 1395.
[5] O. Abdel-Hamid, A. r. Mohamed, H. Jiang, L. Deng, G. Penn and D. Yu, "Convolutional neural networks for speech recognition," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 22, pp. 1533-1545, 2014.
[6] S. Ikbal and H., Bourlard, "Phase autocorrelation derived robust speech features" in Proc. ICASSP, vol. 2, pp. 133-136, 2003.
[7] K. Han, Y. He, D. Bagchi, E. Fosler-Lussier and D. Wang, "Deep neural network based spectral feature mapping for robust speech recognition," in Proc. Interspeech, pp. 2484-2488, 2015.
[8] O. Abdel-Hamid, A. r. Mohamed, H. Jiang and G. Penn, "Applying convolutional neural networks concepts to hybrid NN-HMM model for speech recognition," in 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4277-4280, 2012.
[9] J. Du, Q. Wang, T. Gao, Y. Xu, L. Dai and C.H. Lee, “Robust Speech Recognition with Speech Enhanced Deep Neural Networks”, Interspeech, pp. 616-620, 2014.
[10] X. Feng, Y. Zhang and J. Glass. "Speech feature denoising and dereverberation via deep autoencoders for noisy reverberant speech recognition" In Proc. ICASSP, pp. 1759-1763, 2014.
[11] A. Mohamed, G.E. Dahl and G. Hinton, “Acoustic Modeling Using Deep Belief Networks”, Audio, Speech and Language Processing, IEEE Transactions on, Vol. 20, pp. 14-22, 2011.
[12] T. N. Sainath, A.-r. Mohamed, B. Kingsbury and B. Ramabhadran, "Deep convolutional neural networks for LVCSR," in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 8614-8618, 2013.
[13] O. Abdel-Hamid, L. Deng and D. Yu, "Exploring convolutional neural network structures and optimization techniques for speech recognition," in Interspeech, pp. 3366-3370, 2013.
[14] J.-T. Huang, J. Li and Y. Gong, "An analysis of convolutional neural networks for speech recognition," in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4989-4993, 2015.
[15] D. Palaz,, R. Collobert and M. Magimai Doss, "Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks," in Interspeech, pp. 1766-1770, 2013.
[16] D. Palaz, M. M. Doss and R. Collobert, "Convolutional Neural Networks-based continuous speech recognition using raw speech signal," in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4295-4299, 2015.
[17] D. Palaz, and R. Collobert, "Analysis of cnn-based speech recognition system using raw speech as input," in Proceedings of Interspeech, 2015.
[18] T. N. Sainath, B. Kingsbury, G. Saon, H. Soltau, A.-r. Mohamed, G. Dahl, et al., "Deep convolutional neural networks for large-scale speech tasks," Neural Networks, vol. 64, pp. 39-48, 2015.
[19] Y. Takashima, T. Nakashika, T. Takiguchi and Y. Ariki, "Feature extraction using pre-trained convolutive bottleneck nets for dysarthric speech recognition," in Signal Processing Conference (EUSIPCO), 2015 23rd European, pp. 1411-1415, 2015.
[20] A. Lozano-Diez, R. Zazo-Candil, J. Gonzalez-Dominguez, D. T. Toledano and J. n. Gonz?lez-Rodr?guez, "An end-to-end approach to language identification in short utterances using convolutional neural networks," in INTERSPEECH, 2015.
[21] S. Thomas, S. Ganapathy, G. Saon and H. Soltau, "Analyzing convolutional neural networks for speech activity detection in mismatched acoustic conditions," in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2519-2523, 2014.
[22] R. Yeh, M. Hasegawa-Johnson and M. N. Do, "Stable and symmetric filter convolutional neural network," in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2652-2656, 2016.
[23] T. N. Sainath, O. Vinyals, A. Senior and H. Sak, "Convolutional, long short-term memory, fully connected deep neural networks," in 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4580-4584, 2015.
[24] T. N. Sainath, R. J. Weiss, A. Senior, K. W. Wilson and O. Vinyals, "Learning the speech front-end with raw waveform cldnns," in Proc. Interspeech, 2015.
[25] T. N. Sainath, B. Kingsbury, A.-r. Mohamed and B. Ramabhadran, "Learning filter banks within a deep neural network framework," in Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on, pp. 297-302, 2013.
[26] T. N. Sainath, B. Kingsbury, A.-r. Mohamed, G. E. Dahl, G. Saon, H. Soltau, et al., "Improvements to deep convolutional neural networks for LVCSR," in Automatic Speech Recognition and Understanding (ASRU), 2013 IEEE Workshop on, pp. 315-320, 2013.
[27] Y. Zhao, X. Jin, X. Hu, "Recurrent convolutional neural network for speech processing.", in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
[28] Y. Zhang, W. Chan, N. Jaitly, "Very deep convolutional networks for end-to-end speech recognition.", in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
[29] K. Choi, G. Fazekas, M. Sandler, K.Cho, "Convolutional recurrent neural networks for music classification", in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
[30] Y. Qian, M. Bi, T. Tan and K. Yu, "Very Deep Convolutional Neural Networks for Noise Robust Speech Recognition," in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 24, no. 12, pp. 2263-2276, Dec. 2016.
[31] W. Dai, C. Dai, S. Qu, J. Li, S. Dos, " very deep convolutional neural networks for raw waveforms", in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
[32] H.-G. Hirsch and D. Pearce, "The Aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions," in ASR2000-Automatic Speech Recognition: Challenges for the new Millenium ISCA Tutorial and Research Workshop (ITRW), 2000.
[33] A. Agarwal, E. Akchurin, et al., "An Introduction to Computational Networks and the Computational Networks Toolkit", microsoft technical reports, 2016.