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Aniruddha Tammewar
Researcher at International Institute of Information Technology, Hyderabad
Publications - 14
Citations - 133
Aniruddha Tammewar is an academic researcher from International Institute of Information Technology, Hyderabad. The author has contributed to research in topics: Dependency grammar & Parsing. The author has an hindex of 5, co-authored 11 publications receiving 86 citations.
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IIIT-H System Submission for FIRE2014 Shared Task on Transliterated Search
TL;DR: This paper describes the submission for FIRE 2014 Shared Task on Transliterated Search, which features two sub-tasks: Query word labeling and Mixed-script Ad hoc retrieval for Hindi Song Lyrics.
SEECAT: ASR & Eye-tracking Enabled Computer Assisted Translation
Mercedes García-Martínez,Karan Singla,Aniruddha Tammewar,Bartolomé Mesa-Lao,Ankita Thakur,M A Anusuya,Srinivas Bangalore,Michael Carl +7 more
TL;DR: The integration of automatic speech recognition (ASR) in a CAT workbench testing its real use by human translators while post-editing machine translation (MT) outputs and the use of MT combined with ASR in order to improve recognition accuracy in a workbench integrating eye-tracking functionalities to collect process-oriented information about translators’ performance are investigated.
Proceedings Article
Production Ready Chatbots: Generate if not Retrieve
TL;DR: In this paper, a hybrid model that combines a neural conversational model and a rule-based graph dialogue system that assists users in scheduling reminders through a chat conversation is presented. But the model has high precision and provides a grammatically accurate response but has a low recall.
Posted Content
Annotation of Emotion Carriers in Personal Narratives
TL;DR: An annotation model for identifying emotion carriers in spoken personal narratives, a dataset of PNs in German, is proposed and evaluated and this resource could be used for experiments in the automatic extraction of emotion carriers from PN, a task that could provide further advancements in narrative understanding.
Two-stage Approach for Hindi Dependency Parsing Using MaltParser
TL;DR: The approach towards dependency parsing of Hindi language as a part of Hindi Shared Task on Parsing, COLING 2012 is presented, which includes the effect of using different settings available in Malt Parser following the two-step parsing strategy.