Formally i present my idea in this form: >From my understanding of RBMT ,
The RBMT system contains: - a *SL morphological analyser* - analyses a source language word and provides the morphological information; - a *SL parser* - is a syntax analyser which analyses source language sentences; - a *translator* - used to translate a source language word into the target language; - a *TL morphological generator* - works as a generator of appropriate target language words for the given grammatica information; - a *TL parser* - works as a composer of suitable target language sentences I propose a 6th component of the RBMT system: *sentiment based TL morphological generator* I propose that we do word level sentiment analysis of the source language and targeted language. For the time being i want to work on English-Hindi translation. We do not need a neural network based translation, however for getting the sentiment associated with each word we might use nltk,or develop a character level embedding to just find out the sentiment assosiated with each word,and form a dictionary out of it.I have written a paper on it,and received good results.So basically,during the final application development we will just have the dictionary,with no neural network dependencies. This can easily be done with Python.I just need a good corpus of English and Hindi words(the sentiment datasets are available online). The *sentiment based TL morphological generator *will generate the list of possible words,and we will take that word whose sentiment is closest to the source language word. This is a novel method that has probably not been applied before, and might generate better results. Please provide your valuable feedwork and suggest some necessary changes that needs to be made. Best, Rajarshi On Thu, 27 Feb 2020 at 11:50, Scoop Gracie <scoopgra...@gmail.com> wrote: > It is absolutely fine to use languages you are most comfortable with. > > On Wed, Feb 26, 2020, 22:18 Rajarshi Roychoudhury < > rroychoudhu...@gmail.com> wrote: > >> I need to study more about RBMT to develop an idea of how to preserve >> sentiment while translating, which I think can increase the efficiency of >> translation. It will also help my research , thank you so much for >> suggesting it. Also, will it be okay if I work on languages I am >> comfortable with? Say English-Bengali or Hindi-Bengali >> >> On Thu, Feb 27, 2020, 11:30 Scoop Gracie <scoopgra...@gmail.com> wrote: >> >>> I think it is worth looking into, it is just that anything that needs a >>> neural network is not possible. I'm sure sentiment translation is possible >>> in RBMT too. >>> >>> On Wed, Feb 26, 2020, 21:58 Rajarshi Roychoudhury < >>> rroychoudhu...@gmail.com> wrote: >>> >>>> Ok,then I wont pursue this idea and will look for one in the idea list . >>>> >>>> On Thu, 27 Feb 2020 at 11:10, Scoop Gracie <scoopgra...@gmail.com> >>>> wrote: >>>> >>>>> The main problem is that I don't believe there is a way to send >>>>> information down the pipeline without breaking stuff. >>>>> >>>>> On Wed, Feb 26, 2020, 21:37 Rajarshi Roychoudhury < >>>>> rroychoudhu...@gmail.com> wrote: >>>>> >>>>>> Thank you so much for the feedback,i will try to think of any other >>>>>> way of doing this without using neural networks or propose a new project >>>>>> >>>>>> http://wiki.apertium.org/wiki/Apertium_for_Dummies#The_units_of_translation >>>>>> is an excellent starting point for beginners, however it would be very >>>>>> helpful if you could give an example of the rule based translators as >>>>>> mentioned in the link. >>>>>> Best, >>>>>> Rajarshi Roychoudhury >>>>>> >>>>>> On Thu, 27 Feb 2020 at 10:50, Scoop Gracie <scoopgra...@gmail.com> >>>>>> wrote: >>>>>> >>>>>>> I'm not an expert in this, but given the non-neural nature of >>>>>>> Apertium, this does not seem feasible to me, at least in the way you >>>>>>> described. >>>>>>> >>>>>>> On Wed, Feb 26, 2020, 21:02 Rajarshi Roychoudhury < >>>>>>> rroychoudhu...@gmail.com> wrote: >>>>>>> >>>>>>>> Hi, >>>>>>>> I am Rajarshi Roychoudhury,a second year undergraduate student at >>>>>>>> Jadavpur University,Kolkata,India.I have done many projects in Natural >>>>>>>> Language Processing,mainly focussing on sentiment analysis and machine >>>>>>>> translation. >>>>>>>> >>>>>>>> Most of the machine translation have no explicit preservation on >>>>>>>> the sentiment of the original sentence,as a result a lot of >>>>>>>> information is >>>>>>>> lost during translation,or else it gives an inaccurate translation. >>>>>>>> >>>>>>>> My idea is to incorporate an information about the sentiment of the >>>>>>>> sentence in the hidden layers of the encoder and then send it to a >>>>>>>> decoder.I am writing currently a paper on this topic,and hopefully can >>>>>>>> incorporate my idea into Apertium translation system.Since it is an >>>>>>>> open >>>>>>>> source project,it will be the best platform to reach to people. >>>>>>>> >>>>>>>> Kindly give feedback on whether this can be a possible project >>>>>>>> idea,and if you have any queries on the same.Attached is my resume. >>>>>>>> >>>>>>>> Best, >>>>>>>> Rajarshi Roychoudhury >>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> Apertium-stuff mailing list >>>>>>>> Apertium-stuff@lists.sourceforge.net >>>>>>>> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >>>>>>>> >>>>>>> _______________________________________________ >>>>>>> Apertium-stuff mailing list >>>>>>> Apertium-stuff@lists.sourceforge.net >>>>>>> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >>>>>>> >>>>>> _______________________________________________ >>>>>> Apertium-stuff mailing list >>>>>> Apertium-stuff@lists.sourceforge.net >>>>>> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >>>>>> >>>>> _______________________________________________ >>>>> Apertium-stuff mailing list >>>>> Apertium-stuff@lists.sourceforge.net >>>>> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >>>>> >>>> _______________________________________________ >>>> Apertium-stuff mailing list >>>> Apertium-stuff@lists.sourceforge.net >>>> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >>>> >>> _______________________________________________ >>> Apertium-stuff mailing list >>> Apertium-stuff@lists.sourceforge.net >>> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >>> >> _______________________________________________ >> Apertium-stuff mailing list >> Apertium-stuff@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/apertium-stuff >> > _______________________________________________ > Apertium-stuff mailing list > Apertium-stuff@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/apertium-stuff >
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