Advanced member reading list
来自cslt Wiki
目录
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
- Learning Deep Architectures for AI, Yoshua Bengio
Speech Processing
General
- Spring Handbook of Speech Processing, Ed. Jacob Benesty, M. Mohan Sondhi, Yiteng Huang
- Spoken Language Processing, X.D. Huang,
Acoustics
- Introduction to Digital Signal Processing, Lawrence R. Rabiner and Ronald W. Schafer
- Foundation of acoustics
- Spring Topics in Signal Processing, Microphone Array Processing, Benesty, J.; Chen, J.; Huang, Y
- Signal and System
ASR
- The Application of Hidden Markov Models in Speech Recognition
- Deeplearninginneuralnetworks:Anoverview
