I suppose that an integration is not compatible with the current license of CSLM. GPL cannot be integrated into LGPL. Please, correct me if I'm wrong.
Cheers, Marcello ------- Short from my mobile phone On 04/giu/2012, at 06:12, "Lane Schwartz" <dowob...@gmail.com> wrote: > Excellent! Thank you for releasing this, Holger! > > I know you had mentioned that you'd like to get this integrated into > the decoder. Has anyone from your group been able to work on that? > > Cheers, > Lane > > > On Sun, Jun 3, 2012 at 7:13 PM, Holger Schwenk > <holger.schw...@lium.univ-lemans.fr> wrote: >> I'm happy to announce the availability of a new version of the continuous >> space >> language model (CSLM) toolkit. >> >> Continuous space methods we first introduced by Yoshua Bengio in 2001 [1]. >> The basic idea of this approach is to project the word indices onto a >> continuous space and to use a probability estimator operating on this space. >> Since the resulting probability functions are smooth functions of the word >> representation, better generalization to unknown events can be expected. A >> neural network can be used to simultaneously learn the projection of the >> words >> onto the continuous space and to estimate the n-gram probabilities. This is >> still a n-gram approach, but the LM probabilities are interpolated for any >> possible context of length n-1 instead of backing-off to shorter contexts. >> >> CSLM were initially used in large vocabulary speech recognition systems and >> more >> recently in statistical machine translation. Improvements in the perplexity >> between 10 and 20% relative were reported for many languages and tasks. >> >> >> This version of the CSLM toolkit is a major update of the first release. The >> new features include: >> - full support for short-lists during training and inference. By these >> means, >> the CSLM can be applied to tasks with large vocabularies. >> - very efficient n-best list rescoring. >> - support of graphical extension cards (GPU) from Nvidia. This speeds up >> training by a factor of four with respect to a high-end server with two >> CPUs. >> >> We successfully trained CSLMs on large tasks like NIST OpenMT'12. Training >> on one >> billion words takes less than 24 hours. In our experiments, the CSLM >> achieves >> improvements in the BLEU score of up to two points with respect to a large >> unpruned back-off LM. >> >> A detailed description of the approach can be found in the following >> publications: >> >> [1] Yoshua Bengio and Rejean Ducharme. A neural probabilistic language >> model. >> In NIPS, vol 13, pages 932--938, 2001. >> [2] Holger Schwenk, Continuous Space Language Models; in Computer Speech and >> Language, volume 21, pages 492-518, 2007. >> [3] Holger Schwenk, Continuous Space Language Models For Statistical Machine >> Translation; The Prague Bulletin of Mathematical Linguistics, number 83, >> pages 137-146, 2010. >> [4] Holger Schwenk, Anthony Rousseau and Mohammed Attik; Large, Pruned or >> Continuous Space Language Models on a GPU for Statistical Machine >> Translation, >> in NAACL workshop on the Future of Language Modeling, June 2012. >> >> >> The software is available at http://www-lium.univ-lemans.fr/cslm/. It is >> distributed under GPL v3. >> >> Comments, bug reports, requests for extensions and contributions are >> welcome. >> >> enjoy, >> >> Holger Schwenk >> >> LIUM >> University of Le Mans >> holger.schw...@lium.univ-lemans.fr >> >> >> _______________________________________________ >> Moses-support mailing list >> Moses-support@mit.edu >> http://mailman.mit.edu/mailman/listinfo/moses-support >> > > > > -- > When a place gets crowded enough to require ID's, social collapse is not > far away. It is time to go elsewhere. The best thing about space travel > is that it made it possible to go elsewhere. > -- R.A. Heinlein, "Time Enough For Love" > > _______________________________________________ > Moses-support mailing list > Moses-support@mit.edu > http://mailman.mit.edu/mailman/listinfo/moses-support _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support
