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Found 30 papers, 0 papers with code
On the Importance of Diversity in Question Generation for QA
Automatic question generation (QG) has shown promise as a source of synthetic training data for question answering (QA).
A Major Wordnet for a Minority Language: Scottish Gaelic
We present a new wordnet resource for Scottish Gaelic, a Celtic minority language spoken by about 60, 000 speakers, most of whom live in Northwestern Scotland.
Study on Unsupervised Statistical Machine Translation for Backtranslation
Machine Translation systems have drastically improved over the years for several language pairs.
``My Way of Telling a Story'': Persona based Grounded Story Generation
To this end, we propose five models which are incremental extensions to the baseline model to perform the task at hand.
Storyboarding of Recipes: Grounded Contextual Generation
We introduce a dataset for sequential procedural (how-to) text generation from images in cooking domain.
SSN\_NLP at SemEval-2019 Task 3: Contextual Emotion Identification from Textual Conversation using Seq2Seq Deep Neural Network
We have evaluated our approach on the EmoContext@SemEval2019 dataset and we have obtained the micro-averaged F1 scores as 0. 595 and 0. 6568 for the pre-evaluation dataset and final evaluation test set respectively.
SSN\_NLP at SemEval-2019 Task 6: Offensive Language Identification in Social Media using Traditional and Deep Machine Learning Approaches
Offensive language identification (OLI) in user generated text is automatic detection of any profanity, insult, obscenity, racism or vulgarity that degrades an individual or a group.
Overcoming the bottleneck in traditional assessments of verbal memory: Modeling human ratings and classifying clinical group membership
A final set of three features were used to both predict expert human ratings with a ridge regression model (r = 0. 88) and to differentiate patients from healthy individuals with an ensemble of logistic regression classifiers (accuracy = 76{\%}).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Autosegmental Input Strictly Local Functions
Focusing on the domain of tone, we investigate this ability of ARs using a computationally well-defined notion of locality extended from Chandlee (2014).
Extraction Meets Abstraction: Ideal Answer Generation for Biomedical Questions
The growing number of biomedical publications is a challenge for human researchers, who invest considerable effort to search for relevant documents and pinpointed answers.
Ontology-Based Retrieval \& Neural Approaches for BioASQ Ideal Answer Generation
The ever-increasing magnitude of biomedical information sources makes it difficult and time-consuming for a human researcher to find the most relevant documents and pinpointed answers for a specific question or topic when using only a traditional search engine.
Tackling Code-Switched NER: Participation of CMU
In this paper we describe models that intuitively developed from the data for the shared task Named Entity Recognition on Code-switched Data.
Code-Mixed Question Answering Challenge: Crowd-sourcing Data and Techniques
As a first step towards fostering research which supports CM in NLP applications, we systematically crowd-sourced and curated an evaluation dataset for factoid question answering in three CM languages - Hinglish (Hindi+English), Tenglish (Telugu+English) and Tamlish (Tamil+English) which belong to two language families (Indo-Aryan and Dravidian).
Language Informed Modeling of Code-Switched Text
Code-switching (CS), the practice of alternating between two or more languages in conversations, is pervasive in most multi-lingual communities.
Frustrated, Polite, or Formal: Quantifying Feelings and Tone in Email
We present a novel approach to model human frustration in text.
Memory Augmented Neural Networks for Natural Language Processing
We will present a unified architecture for Memory Augmented Neural Networks (MANN) and discuss the ways in which one can address the external memory and hence read/write from it.
Controlling Human Perception of Basic User Traits
Much of our online communication is text-mediated and, lately, more common with automated agents.
Tackling Biomedical Text Summarization: OAQA at BioASQ 5B
In this paper, we describe our participation in phase B of task 5b of the fifth edition of the annual BioASQ challenge, which includes answering factoid, list, yes-no and summary questions from biomedical data.
Learning Strictly Local Subsequential Functions
We provide an automata-theoretic characterization of the ISL class and theorems establishing how the classes are related to each other and to Strictly Local languages.
