Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Mahata, Sainik Kumar"'
Sentiment analysis has been an active area of research in the past two decades and recently, with the advent of social media, there has been an increasing demand for sentiment analysis on social media texts. Since the social media texts are not in on
Externí odkaz:
http://arxiv.org/abs/2010.10111
Code-mixed texts are widespread nowadays due to the advent of social media. Since these texts combine two languages to formulate a sentence, it gives rise to various research problems related to Natural Language Processing. In this paper, we try to e
Externí odkaz:
http://arxiv.org/abs/2007.14576
In the current work, we explore the enrichment in the machine translation output when the training parallel corpus is augmented with the introduction of sentiment analysis. The paper discusses the preparation of the same sentiment tagged English-Beng
Externí odkaz:
http://arxiv.org/abs/2007.14074
Code-mixing is a phenomenon which arises mainly in multilingual societies. Multilingual people, who are well versed in their native languages and also English speakers, tend to code-mix using English-based phonetic typing and the insertion of anglici
Externí odkaz:
http://arxiv.org/abs/2007.12561
The use of multilingualism in the new generation is widespread in the form of code-mixed data on social media, and therefore a robust translation system is required for catering to the monolingual users, as well as for easier comprehension by languag
Externí odkaz:
http://arxiv.org/abs/1911.03772
In the current work, we present a description of the system submitted to WMT 2018 News Translation Shared task. The system was created to translate news text from Finnish to English. The system used a Character Based Neural Machine Translation model
Externí odkaz:
http://arxiv.org/abs/1908.00323
Autor:
Garain, Avishek, Mahata, Sainik Kumar
This paper describes the system submitted to "Sentiment Analysis at SEPLN (TASS)-2019" shared task. The task includes sentiment analysis of Spanish tweets, where the tweets are in different dialects spoken in Spain, Peru, Costa Rica, Uruguay and Mexi
Externí odkaz:
http://arxiv.org/abs/1908.00321
In the current work, we present a description of the system submitted to WMT 2019 News Translation Shared task. The system was created to translate news text from Lithuanian to English. To accomplish the given task, our system used a Word Embedding b
Externí odkaz:
http://arxiv.org/abs/1908.01349
This paper presents a method to apply Natural Language Processing for normalizing numeronyms to make them understandable by humans. We approach the problem through a two-step mechanism. We make use of the state of the art Levenshtein distance of word
Externí odkaz:
http://arxiv.org/abs/1907.13356
In the present article, we identified the qualitative differences between Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) outputs. We have tried to answer two important questions: 1. Does NMT perform equivalently well with
Externí odkaz:
http://arxiv.org/abs/1812.04898