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 >>>>>>>>>>> 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