New member reading list

Machine Learning

• Deep learning tutotials, LISA lab, University of Montreal

• Deep learning, methods and applications, Li Deng, MS

• Introduction to ML, Nils J. Nilsson, Stanford

• Introduction to Machine Learning, Ethem Alpaydın

• Machine Learning course given by Tom Mitchell

• Neural Networks, A comprehensive foundation, Simon Haykin

• Neumerical optimization, Jorge Nocedal, Stephen J. Wright

• Conjugate Gradient Algorithms in Nonconvex Optimization, Radosaw Pytlak

• Bayesian Reasoning and Machine Learning, David Barber

• Machine Learning, an algorithm perspective, Stephen Marsland

• Neural Petworks for Pattern Recognition, Christopher M. Bishop

Speech Processing

General

• Spring Handbook of Speech Processing, Ed. Jacob Benesty, M. Mohan Sondhi, Yiteng Huang
• Introduction to Digital Signal Processing, Lawrence R. Rabiner and Ronald W. Schafer
• Spoken Language Processing, X.D. Huang,

Acoustics

• Foundation of acoustics
• Spring Topics in Signal Processing, Microphone Array Processing, Benesty, J.; Chen, J.; Huang, Y

ASR

• The Application of Hidden Markov Models in Speech Recognition

Language Processing

• Speech and Language Processing
• Foundation of Natural Language Processing