Oh okay. That should be fine. On Thu, Feb 27, 2020, 08:24 Rajarshi Roychoudhury <rroychoudhu...@gmail.com> wrote:
> No I just need python to get the result, which can be written in a text > file and read using c++. It won't depend on python. > > On Thu, Feb 27, 2020, 21:52 Scoop Gracie <scoopgra...@gmail.com> wrote: > >> Oh, okay. So Python would not be needed at runtime? >> >> On Thu, Feb 27, 2020, 08:20 Rajarshi Roychoudhury < >> rroychoudhu...@gmail.com> wrote: >> >>> I just need to write the dictionary I would get in python in a file and >>> read it using c++. I guess I can use a map to solve my purpose. >>> >>> On Thu, Feb 27, 2020, 21:40 Scoop Gracie <scoopgra...@gmail.com> wrote: >>> >>>> I believe it must use C++, so nltk won't work. >>>> >>>> On Wed, Feb 26, 2020, 23:17 Rajarshi Roychoudhury < >>>> rroychoudhu...@gmail.com> wrote: >>>> >>>>> 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 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