Search Results for author: Ch

Found 30 papers, 0 papers with code

A Major Wordnet for a Minority Language: Scottish Gaelic

no code implementations LREC 2020 G{\'a}bor Bella, Fiona McNeill, Rody Gorman, Caoimhin O Donnaile, Kirsty MacDonald, Ch, Yamini rashekar, Abed Alhakim Freihat, Fausto Giunchiglia

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.

``My Way of Telling a Story'': Persona based Grounded Story Generation

no code implementations WS 2019 Ch, Khyathi u, Shrimai Prabhumoye, Ruslan Salakhutdinov, Alan W. black

To this end, we propose five models which are incremental extensions to the baseline model to perform the task at hand.

Visual Storytelling

SSN\_NLP at SemEval-2019 Task 3: Contextual Emotion Identification from Textual Conversation using Seq2Seq Deep Neural Network

no code implementations SEMEVAL 2019 Senthil Kumar B., Thenmozhi D., Ch, Aravindan rabose, Srinethe Sharavanan

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.


Overcoming the bottleneck in traditional assessments of verbal memory: Modeling human ratings and classifying clinical group membership

no code implementations WS 2019 Ch, Chelsea ler, Peter W. Foltz, Jian Cheng, Jared C. Bernstein, Elizabeth P. Rosenfeld, Alex S. Cohen, Terje B. Holmlund, Brita Elvev{\aa}g

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) +3

Autosegmental Input Strictly Local Functions

no code implementations TACL 2019 Ch, Jane lee, Adam Jardine

Focusing on the domain of tone, we investigate this ability of ARs using a computationally well-defined notion of locality extended from Chandlee (2014).

Ontology-Based Retrieval \& Neural Approaches for BioASQ Ideal Answer Generation

no code implementations WS 2018 Ashwin Naresh Kumar, Harini Kesavamoorthy, Madhura Das, Pramati Kalwad, Ch, Khyathi u, Teruko Mitamura, Eric Nyberg

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.

Abstractive Text Summarization Answer Generation +5

Extraction Meets Abstraction: Ideal Answer Generation for Biomedical Questions

no code implementations WS 2018 Yutong Li, Nicholas Gekakis, Qiuze Wu, Boyue Li, Ch, Khyathi u, Eric Nyberg

The growing number of biomedical publications is a challenge for human researchers, who invest considerable effort to search for relevant documents and pinpointed answers.

Abstractive Text Summarization Answer Generation +5

Code-Mixed Question Answering Challenge: Crowd-sourcing Data and Techniques

no code implementations WS 2018 Ch, Khyathi u, Ekaterina Loginova, Vishal Gupta, Josef van Genabith, G{\"u}nter Neumann, Manoj Chinnakotla, Eric Nyberg, Alan W. black

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).

Question Answering Sentence

Tackling Code-Switched NER: Participation of CMU

no code implementations WS 2018 Parvathy Geetha, Ch, Khyathi u, Alan W. black

In this paper we describe models that intuitively developed from the data for the shared task Named Entity Recognition on Code-switched Data.

named-entity-recognition Named Entity Recognition +3

Language Informed Modeling of Code-Switched Text

no code implementations WS 2018 Ch, Khyathi u, Thomas Manzini, Sumeet Singh, Alan W. black

Code-switching (CS), the practice of alternating between two or more languages in conversations, is pervasive in most multi-lingual communities.

Language Modelling Machine Translation +2

Memory Augmented Neural Networks for Natural Language Processing

no code implementations EMNLP 2017 Caglar Gulcehre, Ch, Sarath ar

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.

Language Modelling Question Answering +1

Tackling Biomedical Text Summarization: OAQA at BioASQ 5B

no code implementations WS 2017 Khyathi u, Aakanksha Naik, Ch, Aditya rasekar, Zi Yang, Niloy Gupta, Eric Nyberg

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.

Answer Generation Clustering +5

Learning Strictly Local Subsequential Functions

no code implementations TACL 2014 Ch, Jane lee, R{\'e}mi Eyraud, Jeffrey Heinz

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.

Cannot find the paper you are looking for? You can Submit a new open access paper.