no code implementations • ACL 2022 • Carolina Cuesta-Lazaro, Animesh Prasad, Trevor Wood
We present a complete pipeline to extract characters in a novel and link them to their direct-speech utterances.
1 code implementation • 26 May 2023 • Yue Feng, Yunlong Jiao, Animesh Prasad, Nikolaos Aletras, Emine Yilmaz, Gabriella Kazai
Further, it employs a fulfillment representation layer for learning how many task attributes have been fulfilled in the dialogue, an importance predictor component for calculating the importance of task attributes.
no code implementations • 13 Feb 2022 • Mateusz Lajszczak, Animesh Prasad, Arent van Korlaar, Bajibabu Bollepalli, Antonio Bonafonte, Arnaud Joly, Marco Nicolis, Alexis Moinet, Thomas Drugman, Trevor Wood, Elena Sokolova
This paper presents a novel data augmentation technique for text-to-speech (TTS), that allows to generate new (text, audio) training examples without requiring any additional data.
1 code implementation • COLING 2020 • Akshay Bhola, Kishaloy Halder, Animesh Prasad, Min-Yen Kan
We introduce a deep learning model to learn the set of enumerated job skills associated with a job description.
no code implementations • NAACL 2019 • Animesh Prasad, Min-Yen Kan
Graph Convolutional Networks (GCNs) are a class of spectral clustering techniques that leverage localized convolution filters to perform supervised classification directly on graphical structures.
no code implementations • WS 2019 • Animesh Prasad, Chenglei Si, Min-Yen Kan
Datasets are integral artifacts of empirical scientific research.
2 code implementations • 18 Nov 2018 • Xuan Su, Animesh Prasad, Min-Yen Kan, Kazunari Sugiyama
Citation function and provenance are two cornerstone tasks in citation analysis.
1 code implementation • COLING 2018 • Shenhao Jiang, Animesh Prasad, Min-Yen Kan, Kazunari Sugiyama
Identifying emergent research trends is a key issue for both primary researchers as well as secondary research managers.
no code implementations • 17 Jul 2018 • Animesh Prasad, Hervé Déjean, Jean-Luc Meunier, Max Weidemann, Johannes Michael, Gundram Leifert
In this report, we present our findings from benchmarking experiments for information extraction on historical handwritten marriage records Esposalles from IEHHR - ICDAR 2017 robust reading competition.
no code implementations • SEMEVAL 2017 • Animesh Prasad, Min-Yen Kan
We describe an end-to-end pipeline processing approach for SemEval 2017{'}s Task 10 to extract keyphrases and their relations from scientific publications.