“Public Research Tools”版本间的差异

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http://www1.icsi.berkeley.edu/Speech/papers/qio/
 
http://www1.icsi.berkeley.edu/Speech/papers/qio/
  
3. RNN training
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3. LTSM/RNN training, GPU&deep supported
  
 
http://sourceforge.net/projects/currennt/
 
http://sourceforge.net/projects/currennt/
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4. Sequence CRF
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http://research.microsoft.com/en-us/projects/scarf/
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5.  RNNLM: RNN LM toolkit
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http://www.fit.vutbr.cz/~imikolov/rnnlm/
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6. RWTHLM: RNN LTSM toolkit
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http://www-i6.informatik.rwth-aachen.de/web/Software/rwthlm.php
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7. cslm: NN LM, GPU supported
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http://www-lium.univ-lemans.fr/~cslm/
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8. nplm: NN LM, large scale data
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http://nlg.isi.edu/software/nplm/
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=Machine Learning=
 
=Machine Learning=

2014年9月23日 (二) 02:40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/

3. LTSM/RNN training, GPU&deep supported

http://sourceforge.net/projects/currennt/

4. Sequence CRF

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

5. RNNLM: RNN LM toolkit

http://www.fit.vutbr.cz/~imikolov/rnnlm/

6. RWTHLM: RNN LTSM toolkit

http://www-i6.informatik.rwth-aachen.de/web/Software/rwthlm.php

7. cslm: NN LM, GPU supported

http://www-lium.univ-lemans.fr/~cslm/

8. nplm: NN LM, large scale data

http://nlg.isi.edu/software/nplm/



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

14. pylearn2

http://deeplearning.net/software/pylearn2/

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