2014年6月20日 (五) 00:57的版本

Speech recognition

1. Noise robustness

http://www1.icsi.berkeley.edu/Speech/papers/gelbart-ms/pointers/

2. Qualcomm-ICSI-OGI front end http://www1.icsi.berkeley.edu/Speech/papers/qio/

Machine Learning

1. general Bayesian inference: doc and tool

http://ksvanhorn.com/bayes/free-bayes-software.html

2. The Variantional Bayesian toolkit:

http://www.gatsby.ucl.ac.uk/vbayes/vbsoftware.html

The sampling based Bayesian approach can be obtained here:

http://www.mrc-bsu.cam.ac.uk/bugs/

3. Topic models from David Blei

http://www.cs.princeton.edu/~blei/topicmodeling.html

4. MCMC approaches also here

http://www.mppmu.mpg.de/bat/

http://www.mpe.mpg.de/~aws/BayesForum_201204_KK.pdf

5. Topic models Biography

http://www.cs.princeton.edu/~mimno/topics.html

6. Gibbs LDA

http://gibbslda.sourceforge.net/

7. Tools for DPMM

Jacobei

https://github.com/jacobeisenstein/DPMM

Sickit

http://scikit-learn.org/0.11/index.html

Hains

http://code.google.com/p/haines/

8. Sparse SVMs

http://www.enm.bris.ac.uk/staff/xkh/

9. Lasso

http://www-stat.stanford.edu/~tibs/lasso.html

10. Sparse LU

http://crd-legacy.lbl.gov/~xiaoye/SuperLU/

11. Ensemble SVM

http://homes.esat.kuleuven.be/~claesenm/ensemblesvm/

12. Online learning toolkit

http://www.cais.ntu.edu.sg/~chhoi/libol/

13. VBEM-GMM

http://www.cs.ubc.ca/~murphyk/Software/VBEMGMM/index.html

NLP toolkits and resources

1. Stanford tools

http://nlp.stanford.edu/software/

2. Traditional Chinese public dictionary and statistics

http://www.edu.tw/files/site_content/m0001/pin/yu7.htm?open

3. Idiom Traditional Chinese public words

http://dict.idioms.moe.edu.tw/cydic/index.htm

4. RNN toolkit from microsoft

http://research.microsoft.com/en-us/projects/rnn/

5. A bunch of resources

http://www-nlp.stanford.edu/links/statnlp.html

SID toolits

1. Alize from Avignon

http://mistral.univ-avignon.fr/download_en.html

2. Idiap

https://github.com/bioidiap/xbob.spkrec

http://www.idiap.ch/~marcel/professional/Resources.html

People you may want to follow

1. Dong Yu, MS

http://research.microsoft.com/en-us/people/dongyu/

2. Geoffrey E. Hinton, U. Toronto

http://www.cs.toronto.edu/~hinton/

3. Deng Li, MS

http://research.microsoft.com/en-us/people/deng/

4. Tara Sainath, IBM

http://www.researchgate.net/profile/Tara_Sainath/publications/

http://www.informatik.uni-trier.de/~ley/pers/hd/s/Sainath:Tara_N=.html

5. Daniel Povey, JHU

http://www.danielpovey.com/

6. Patrick Kenny, CRIM

http://www.crim.ca/perso/patrick.kenny/

7. Nelson Morgan, ICSI Berkley

http://www1.icsi.berkeley.edu/~morgan/