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Today's Topics:
1. Re: moses server segmentation fault (core dumped) (Barry Haddow)
2. Re: Fwd: Moses-support Digest, Vol 90, Issue 19 (Barry Haddow)
----------------------------------------------------------------------
Message: 1
Date: Thu, 10 Apr 2014 18:25:46 +0100
From: Barry Haddow <bhaddow@staffmail.ed.ac.uk>
Subject: Re: [Moses-support] moses server segmentation fault (core
dumped)
To: kamel nebhi <k.nebhi@sheffield.ac.uk>, moses-support
<moses-support@mit.edu>
Message-ID: <5346D41A.2020106@staffmail.ed.ac.uk>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Hi Kamel
Could you try running the model with command-line Moses to see if the
same problem happens?
If you still get a seg-fault and no error message, would you be able to
run Moses in a debugger to get a stack trace?
cheers - Barry
On 07/04/14 18:25, kamel nebhi wrote:
> Hi,
>
> I try to install mosesserver on localhost. I have installed xml-rpc
> and rebuild moses with no problem.
>
> Next i use this command to run the server :
> *~/mosesdecoder/bin/mosesserver -f working/model/moses.ini
> --server-port 8999*
> *
> *
> But it failed with this message :
>
> Defined parameters (per moses.ini or switch):
> config: /home/kamelnebhi/recaser/training/moses.ini
> distortion-limit: 6
> feature: UnknownWordPenalty WordPenalty PhrasePenalty
> PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0 Distortion KENLM lazyken=0 name=LM0
> factor=0 path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> input-factors: 0
> mapping: 0 T 0
> weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2
> TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5
> /home/kamelnebhi/mosesdecoder/bin
> line=UnknownWordPenalty
> FeatureFunction: UnknownWordPenalty0 start: 0 end: 0
> line=WordPenalty
> FeatureFunction: WordPenalty0 start: 1 end: 1
> line=PhrasePenalty
> FeatureFunction: PhrasePenalty0 start: 2 end: 2
> line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0
> FeatureFunction: TranslationModel0 start: 3 end: 6
> line=Distortion
> FeatureFunction: Distortion0 start: 7 end: 7
> line=KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> FeatureFunction: LM0 start: 8 end: 8
> Loading the LM will be faster if you build a binary file.
> Reading /home/kamelnebhi/recaser/training//cased.srilm.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> *The ARPA file is missing <unk>. Substituting log10 probability -100.
> ***************************************************************************************************
> Loading UnknownWordPenalty0
> Loading WordPenalty0
> Loading PhrasePenalty0
> Loading Distortion0
> Loading LM0
> Loading TranslationModel0
> Start loading text SCFG phrase table. Moses format : [3.69361] seconds
> Reading /home/kamelnebhi/recaser/training/phrase-table.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> ****************************************************************************************************
> Erreur de segmentation (core dumped)
> root@kamelnebhi-MacBookPro:/home/kamelnebhi#
> /home/kamelnebhi/mosesdecoder/bin/mosesserver -f
> /home/kamelnebhi/recaser/training/moses.ini --server-port 80
> Defined parameters (per moses.ini or switch):
> config: /home/kamelnebhi/recaser/training/moses.ini
> distortion-limit: 6
> feature: UnknownWordPenalty WordPenalty PhrasePenalty
> PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0 Distortion KENLM lazyken=0 name=LM0
> factor=0 path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> input-factors: 0
> mapping: 0 T 0
> weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2
> TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5
> /home/kamelnebhi/mosesdecoder/bin
> line=UnknownWordPenalty
> FeatureFunction: UnknownWordPenalty0 start: 0 end: 0
> line=WordPenalty
> FeatureFunction: WordPenalty0 start: 1 end: 1
> line=PhrasePenalty
> FeatureFunction: PhrasePenalty0 start: 2 end: 2
> line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0
> FeatureFunction: TranslationModel0 start: 3 end: 6
> line=Distortion
> FeatureFunction: Distortion0 start: 7 end: 7
> line=KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> FeatureFunction: LM0 start: 8 end: 8
> Loading the LM will be faster if you build a binary file.
> Reading /home/kamelnebhi/recaser/training//cased.srilm.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> *The ARPA file is missing <unk>. Substituting log10 probability -100.
> ***************************************************************************************************
> Loading UnknownWordPenalty0
> Loading WordPenalty0
> Loading PhrasePenalty0
> Loading Distortion0
> Loading LM0
> Loading TranslationModel0
> Start loading text SCFG phrase table. Moses format : [3.69152] seconds
> Reading /home/kamelnebhi/recaser/training/phrase-table.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> ****************************************************************************************************
> Segmentation fault (core dumped)
>
> *Thanks for your help*
> *
> *
>
>
> _______________________________________________
> Moses-support mailing list
> Moses-support@mit.edu
> http://mailman.mit.edu/mailman/listinfo/moses-support
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.
------------------------------
Message: 2
Date: Thu, 10 Apr 2014 18:28:32 +0100
From: Barry Haddow <bhaddow@staffmail.ed.ac.uk>
Subject: Re: [Moses-support] Fwd: Moses-support Digest, Vol 90, Issue
19
To: Lakshya <elekshman@gmail.com>, moses-support@mit.edu, Hieu Hoang
<Hieu.Hoang@ed.ac.uk>
Message-ID: <5346D4C0.5090604@staffmail.ed.ac.uk>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Hi Lakysha
There has been very little change in the moses server.
Try running the following before you launch moses server
export XMLRPC_TRACE_XML=1
and you should get a dump of the xmlrpc messages. This may help you
debug the problem,
cheers - Barry
On 09/04/14 20:47, Lakshya wrote:
> Hi Everybody,
>
> I am also facing problem with Mosesdecoder.v211 moseserver. I have
> compiled the moseserver with out any error and the moseserver is
> listenening to the port also. But when a translation request is going
> from the interface, there is no responds from the mosesserver.
>
> I am getting the folowing exception..
> org.apache.xmlrpc.XmlRpcException: Failed to read server's response:
> Connection refused
>
> Is there any difference in the moseswerver connection of Mosesdecoder
> Release 1.0 and Mosesdecoder.V211. ?
>
>
>
> could anybody please clarify these doubts and how can I establish the
> moseserver connection..
>
>
> Regards
> Lakshya
>
> Message: 1
> Date: Mon, 7 Apr 2014 18:25:35 +0100
> From: kamel nebhi <k.nebhi@sheffield.ac.uk
> <mailto:k.nebhi@sheffield.ac.uk>>
> Subject: [Moses-support] moses server segmentation fault (core dumped)
> To: moses-support <moses-support@mit.edu <mailto:moses-support@mit.edu>>
> Message-ID:
> <CAG66Y3c2UFq5+
> 2w4eV00RrwVrMWTtVxpQ7=jgXFwNG+aFnRjCA@mail.gmail.com
> <mailto:jgXFwNG%2BaFnRjCA@mail.gmail.com>>
> Content-Type: text/plain; charset="utf-8"
>
> Hi,
>
> I try to install mosesserver on localhost. I have installed xml-rpc and
> rebuild moses with no problem.
>
> Next i use this command to run the server :
> *~/mosesdecoder/bin/mosesserver
> -f working/model/moses.ini --server-port 8999*
>
> But it failed with this message :
>
> Defined parameters (per moses.ini or switch):
> config: /home/kamelnebhi/recaser/training/moses.ini
> distortion-limit: 6
> feature: UnknownWordPenalty WordPenalty PhrasePenalty
> PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4
> path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0
> output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> input-factors: 0
> mapping: 0 T 0
> weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2
> TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5
> /home/kamelnebhi/mosesdecoder/bin
> line=UnknownWordPenalty
> FeatureFunction: UnknownWordPenalty0 start: 0 end: 0
> line=WordPenalty
> FeatureFunction: WordPenalty0 start: 1 end: 1
> line=PhrasePenalty
> FeatureFunction: PhrasePenalty0 start: 2 end: 2
> line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0
> FeatureFunction: TranslationModel0 start: 3 end: 6
> line=Distortion
> FeatureFunction: Distortion0 start: 7 end: 7
> line=KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> FeatureFunction: LM0 start: 8 end: 8
> Loading the LM will be faster if you build a binary file.
> Reading /home/kamelnebhi/recaser/training//cased.srilm.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> *The ARPA file is missing <unk>. Substituting log10 probability -100.
> ***************************************************************************************************
> Loading UnknownWordPenalty0
> Loading WordPenalty0
> Loading PhrasePenalty0
> Loading Distortion0
> Loading LM0
> Loading TranslationModel0
> Start loading text SCFG phrase table. Moses format : [3.69361] seconds
> Reading /home/kamelnebhi/recaser/training/phrase-table.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> ****************************************************************************************************
> Erreur de segmentation (core dumped)
> root@kamelnebhi-MacBookPro:/home/kamelnebhi#
> /home/kamelnebhi/mosesdecoder/bin/mosesserver -f
> /home/kamelnebhi/recaser/training/moses.ini --server-port 80
> Defined parameters (per moses.ini or switch):
> config: /home/kamelnebhi/recaser/training/moses.ini
> distortion-limit: 6
> feature: UnknownWordPenalty WordPenalty PhrasePenalty
> PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4
> path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0
> output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> input-factors: 0
> mapping: 0 T 0
> weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2
> TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5
> /home/kamelnebhi/mosesdecoder/bin
> line=UnknownWordPenalty
> FeatureFunction: UnknownWordPenalty0 start: 0 end: 0
> line=WordPenalty
> FeatureFunction: WordPenalty0 start: 1 end: 1
> line=PhrasePenalty
> FeatureFunction: PhrasePenalty0 start: 2 end: 2
> line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0
> FeatureFunction: TranslationModel0 start: 3 end: 6
> line=Distortion
> FeatureFunction: Distortion0 start: 7 end: 7
> line=KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> FeatureFunction: LM0 start: 8 end: 8
> Loading the LM will be faster if you build a binary file.
> Reading /home/kamelnebhi/recaser/training//cased.srilm.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> *The ARPA file is missing <unk>. Substituting log10 probability -100.
> ***************************************************************************************************
> Loading UnknownWordPenalty0
> Loading WordPenalty0
> Loading PhrasePenalty0
> Loading Distortion0
> Loading LM0
> Loading TranslationModel0
> Start loading text SCFG phrase table. Moses format : [3.69152] seconds
> Reading /home/kamelnebhi/recaser/training/phrase-table.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> ****************************************************************************************************
> Segmentation fault (core dumped)
>
> *Thanks for your help*
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL:
> http://mailman.mit.edu/mailman/private/moses-support/attachments/20140407/82302fab/attachment-0001.htm
>
> ------------------------------
>
> ---------- Forwarded message ----------
> From: <moses-support-request@mit.edu
> <mailto:moses-support-request@mit.edu>>
> Date: Tue, Apr 8, 2014 at 3:57 AM
> Subject: Moses-support Digest, Vol 90, Issue 19
> To: moses-support@mit.edu <mailto:moses-support@mit.edu>
>
>
> Send Moses-support mailing list submissions to
> moses-support@mit.edu <mailto:moses-support@mit.edu>
>
> To subscribe or unsubscribe via the World Wide Web, visit
> http://mailman.mit.edu/mailman/listinfo/moses-support
> or, via email, send a message with subject or body 'help' to
> moses-support-request@mit.edu <mailto:moses-support-request@mit.edu>
>
> You can reach the person managing the list at
> moses-support-owner@mit.edu <mailto:moses-support-owner@mit.edu>
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of Moses-support digest..."
>
>
> Today's Topics:
>
> 1. moses server segmentation fault (core dumped) (kamel nebhi)
> 2. Re: Monolingual Word alignment (Philipp Koehn)
> 3. Call for Participation: Automatic and Manual Metrics for
> Operational Translation Evaluation (Lucia Specia)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 7 Apr 2014 18:25:35 +0100
> From: kamel nebhi <k.nebhi@sheffield.ac.uk
> <mailto:k.nebhi@sheffield.ac.uk>>
> Subject: [Moses-support] moses server segmentation fault (core dumped)
> To: moses-support <moses-support@mit.edu <mailto:moses-support@mit.edu>>
> Message-ID:
>
> <CAG66Y3c2UFq5+2w4eV00RrwVrMWTtVxpQ7=jgXFwNG+aFnRjCA@mail.gmail.com
> <mailto:jgXFwNG%2BaFnRjCA@mail.gmail.com>>
> Content-Type: text/plain; charset="utf-8"
>
> Hi,
>
> I try to install mosesserver on localhost. I have installed xml-rpc and
> rebuild moses with no problem.
>
> Next i use this command to run the server :
> *~/mosesdecoder/bin/mosesserver
> -f working/model/moses.ini --server-port 8999*
>
> But it failed with this message :
>
> Defined parameters (per moses.ini or switch):
> config: /home/kamelnebhi/recaser/training/moses.ini
> distortion-limit: 6
> feature: UnknownWordPenalty WordPenalty PhrasePenalty
> PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4
> path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0
> output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> input-factors: 0
> mapping: 0 T 0
> weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2
> TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5
> /home/kamelnebhi/mosesdecoder/bin
> line=UnknownWordPenalty
> FeatureFunction: UnknownWordPenalty0 start: 0 end: 0
> line=WordPenalty
> FeatureFunction: WordPenalty0 start: 1 end: 1
> line=PhrasePenalty
> FeatureFunction: PhrasePenalty0 start: 2 end: 2
> line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0
> FeatureFunction: TranslationModel0 start: 3 end: 6
> line=Distortion
> FeatureFunction: Distortion0 start: 7 end: 7
> line=KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> FeatureFunction: LM0 start: 8 end: 8
> Loading the LM will be faster if you build a binary file.
> Reading /home/kamelnebhi/recaser/training//cased.srilm.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> *The ARPA file is missing <unk>. Substituting log10 probability -100.
> ***************************************************************************************************
> Loading UnknownWordPenalty0
> Loading WordPenalty0
> Loading PhrasePenalty0
> Loading Distortion0
> Loading LM0
> Loading TranslationModel0
> Start loading text SCFG phrase table. Moses format : [3.69361] seconds
> Reading /home/kamelnebhi/recaser/training/phrase-table.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> ****************************************************************************************************
> Erreur de segmentation (core dumped)
> root@kamelnebhi-MacBookPro:/home/kamelnebhi#
> /home/kamelnebhi/mosesdecoder/bin/mosesserver -f
> /home/kamelnebhi/recaser/training/moses.ini --server-port 80
> Defined parameters (per moses.ini or switch):
> config: /home/kamelnebhi/recaser/training/moses.ini
> distortion-limit: 6
> feature: UnknownWordPenalty WordPenalty PhrasePenalty
> PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4
> path=/home/kamelnebhi/recaser/training/phrase-table.gz input-factor=0
> output-factor=0 Distortion KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> input-factors: 0
> mapping: 0 T 0
> weight: UnknownWordPenalty0= 1 WordPenalty0= -1 PhrasePenalty0= 0.2
> TranslationModel0= 0.2 0.2 0.2 0.2 Distortion0= 0.3 LM0= 0.5
> /home/kamelnebhi/mosesdecoder/bin
> line=UnknownWordPenalty
> FeatureFunction: UnknownWordPenalty0 start: 0 end: 0
> line=WordPenalty
> FeatureFunction: WordPenalty0 start: 1 end: 1
> line=PhrasePenalty
> FeatureFunction: PhrasePenalty0 start: 2 end: 2
> line=PhraseDictionaryMemory name=TranslationModel0 table-limit=20
> num-features=4 path=/home/kamelnebhi/recaser/training/phrase-table.gz
> input-factor=0 output-factor=0
> FeatureFunction: TranslationModel0 start: 3 end: 6
> line=Distortion
> FeatureFunction: Distortion0 start: 7 end: 7
> line=KENLM lazyken=0 name=LM0 factor=0
> path=/home/kamelnebhi/recaser/training//cased.srilm.gz order=3
> FeatureFunction: LM0 start: 8 end: 8
> Loading the LM will be faster if you build a binary file.
> Reading /home/kamelnebhi/recaser/training//cased.srilm.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> *The ARPA file is missing <unk>. Substituting log10 probability -100.
> ***************************************************************************************************
> Loading UnknownWordPenalty0
> Loading WordPenalty0
> Loading PhrasePenalty0
> Loading Distortion0
> Loading LM0
> Loading TranslationModel0
> Start loading text SCFG phrase table. Moses format : [3.69152] seconds
> Reading /home/kamelnebhi/recaser/training/phrase-table.gz
> ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100
> ****************************************************************************************************
> Segmentation fault (core dumped)
>
> *Thanks for your help*
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL:
> http://mailman.mit.edu/mailman/private/moses-support/attachments/20140407/82302fab/attachment-0001.htm
>
> ------------------------------
>
> Message: 2
> Date: Mon, 7 Apr 2014 16:00:47 -0400
> From: Philipp Koehn <pkoehn@inf.ed.ac.uk <mailto:pkoehn@inf.ed.ac.uk>>
> Subject: Re: [Moses-support] Monolingual Word alignment
> To: Mostafa Dehghani <dehghani.mostafa@gmail.com
> <mailto:dehghani.mostafa@gmail.com>>
> Cc: "moses-support@mit.edu <mailto:moses-support@mit.edu>"
> <moses-support@mit.edu <mailto:moses-support@mit.edu>>
> Message-ID:
>
> <CAAFADDBXoZv7=u5RqJaY3brfWOB92yWKRvfeKdz6yrx29m78DA@mail.gmail.com
> <mailto:u5RqJaY3brfWOB92yWKRvfeKdz6yrx29m78DA@mail.gmail.com>>
> Content-Type: text/plain; charset=ISO-8859-1
>
> Hi,
>
> this outcome is not that surprising to me.
>
> If you align identical sentences, then translating each word to itself
> is a pretty good model.
>
> Since your goal is paraphrasing words into synonyms, you should
> rather use methods such as the one proposed by Bannard and
> Callison-Burch: http://acl.ldc.upenn.edu/P/P05/P05-1074.pdf
>
> -phi
>
> On Sun, Apr 6, 2014 at 11:11 AM, Mostafa Dehghani
> <dehghani.mostafa@gmail.com <mailto:dehghani.mostafa@gmail.com>> wrote:
> > Dear all,
> >
> > I am working on a method for Multilingual Information Retrieval. In my
> > method I expand the text of each document by probabilistically
> translating
> > its words to other languages' words (interlingual expansion).
> However, to
> > pass some axioms, I need to expand text of each document in its own
> language
> > (intralingual expansion). So, beside bilingual word alignments, I need
> > monolingual word alignments table (that probably contains the
> alignment of
> > each word to the words those are related/concurred with that word).
> To do
> > so, I used one side of each language sentences and their copy as
> parallel
> > corpus. Then I used the following command:
> >
> >
> > train-model.perl -root-dir train -corpus corpus/fr-fr -f fr1 -e fr2
> > -alignment grow-diag-final-and -reordering msd-bidirectional-fe
> > -external-bin-dir externalbin -last-step 4
> >
> >
> > such that fr-fr.fr1 fr-fr.fr2 are the same files containing French
> > sentences.
> > However, I got f2e and e2f files that are only contain alignments of
> each
> > word to itself with probability of 1.
> > I am wondering is there any parameter that I should set to achieve words
> > alignments (e2f/f2e) those are proper for intralingual expansion?
> >
> > Regards,
> >
> > --
> > Mostafa
> > ,
> >
> > http://khorshid.ut.ac.ir/~m.dehghani
> <http://khorshid.ut.ac.ir/%7Em.dehghani>
> >
> > _______________________________________________
> > Moses-support mailing list
> > Moses-support@mit.edu <mailto:Moses-support@mit.edu>
> > http://mailman.mit.edu/mailman/listinfo/moses-support
> >
>
>
> ------------------------------
>
> Message: 3
> Date: Mon, 7 Apr 2014 23:27:07 +0100
> From: Lucia Specia <lspecia@gmail.com <mailto:lspecia@gmail.com>>
> Subject: [Moses-support] Call for Participation: Automatic and Manual
> Metrics for Operational Translation Evaluation
> To: moses-support@mit.edu <mailto:moses-support@mit.edu>,
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> Dear all,
>
> This workshop may be relevant for those of you interested in MT evaluation
> metrics.
>
> ----
>
> Automatic and Manual Metrics for Operational Translation Evaluation
>
> http://mte2014.github.io/
>
> 26 May 2014
>
> Workshop at Language Resources and Evaluation Conference (LREC) 2014
>
> http://lrec2014.lrec-conf.org
>
> In brief:
>
> We invite you to join us for an interesting day of work (and play!) as we
> discuss metrics for machine translation quality assessment and participate
> in some hands-on task-based translation evaluation.
>
> This workshop on Automatic and Manual Metrics for Operational Translation
> Evaluation (MTE 2014) will be a full-day LREC workshop to be held on
> Monday, May 26, 2014 in Reykjavik, Iceland. The format of MTE 2014 will be
> interactive and energizing: a half-day of short presentations and
> discussion of recent work on machine translation quality assessment,
> followed by a half-day of hands-on collaborative work with MT metrics that
> show promise for the prediction of task suitability of MT output. The
> afternoon hands-on work will follow from the morning's presentations, with
> some of the hands-on exercises developed directly from the submissions to
> the workshop.
>
> Details:
>
> While a significant body of work has been done by the machine translation
> (MT) research community towards the development and meta-evaluation of
> automatic metrics to assess overall MT quality, less attention has been
> dedicated to more operational evaluation metrics aimed at testing whether
> translations are adequate within a specific context: purpose, end-user,
> task, etc., and why the MT system fails in some cases. Both of these can
> benefit from some form of manual analysis. Most work in this area is
> limited to productivity tests (e.g. contrasting time for human translation
> and MT post-editing). A few initiatives consider more detailed metrics for
> the problem, which can also be used to understand and diagnose errors
> in MT
> systems. These include the Multidimensional Quality Metrics (MQM) recently
> proposed by the EU F7 project QTLaunchPad, the TAUS Dynamic Quality
> Framework, and past projects such as FEMTI, EAGLES and ISLE. Some of these
> metrics are also applicable to human translation evaluation. A number of
> task-based metrics have also been proposed for applications such as topic
> ID / triage and reading comprehension. The purpose of this workshop is to
> bring together representatives from academia, industry and government
> institutions to discuss and assess metrics for manual and automatic
> quality
> evaluation, with an eye toward how they might be leveraged or further
> developed into task-based metrics for more objective "fitness for purpose"
> assessment. We will also consider comparisons to well-established metrics
> for automatic evaluation such as BLEU, METEOR and others, including
> reference-less metrics for quality prediction. The workshop will benefit
> from datasets already collected and manually annotated for translation
> errors by the QTLaunchPad project (http://www.qt21.eu/launchpad/) and will
> cover concepts from many the metrics proposed by participants in the
> half-day of hands-on tasks.
>
> Up-to-the-minute information and (most importantly) Registration:
>
> Additional details and schedule will be posted at the workshop website
> http://mte2014.github.io/ as they become available. Register to attend via
> the LREC registration site at
> http://lrec2014.lrec-conf.org/en/registration/
> .
>
> We look forward to seeing you there!
>
> The MTE 2014 Organizing Committee
>
> Keith J. Miller (MITRE)
>
> Lucia Specia (University of Sheffield)
>
> Kim Harris (GALA and text & form)
>
> Stacey Bailey (MITRE)
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