Rohit Prasad


2013

pdf bib
Semi-Supervised Word Sense Disambiguation for Mixed-Initiative Conversational Spoken Language Translation
Sankaranarayanan Ananthakrishnan | Sanjika Hewavitharana | Rohit Kumar | Enoch Kan | Rohit Prasad | Prem Natarajan
Proceedings of Machine Translation Summit XIV: Papers

2012

pdf bib
Automatic Tune Set Generation for Machine Translation with Limited Indomain Data
Jinying Chen | Jacob Devlin | Huaigu Cao | Rohit Prasad | Premkumar Natarajan
Proceedings of the 16th Annual conference of the European Association for Machine Translation

pdf bib
Automatic Detection of Psychological Distress Indicators and Severity Assessment from Online Forum Posts
Shirin Saleem | Rohit Prasad | Shiv Vitaladevuni | Maciej Pacula | Michael Crystal | Brian Marx | Denise Sloan | Jennifer Vasterling | Theodore Speroff
Proceedings of COLING 2012

pdf bib
Active error detection and resolution for speech-to-speech translation
Rohit Prasad | Rohit Kumar | Sankaranarayanan Ananthakrishnan | Wei Chen | Sanjika Hewavitharana | Matthew Roy | Frederick Choi | Aaron Challenner | Enoch Kan | Arvid Neelakantan | Prem Natarajan
Proceedings of the 9th International Workshop on Spoken Language Translation: Papers

We describe a novel two-way speech-to-speech (S2S) translation system that actively detects a wide variety of common error types and resolves them through user-friendly dialog with the user(s). We present algorithms for detecting out-of-vocabulary (OOV) named entities and terms, sense ambiguities, homophones, idioms, ill-formed input, etc. and discuss novel, interactive strategies for recovering from such errors. We also describe our approach for prioritizing different error types and an extensible architecture for implementing these decisions. We demonstrate the efficacy of our system by presenting analysis on live interactions in the English-to-Iraqi Arabic direction that are designed to invoke different error types for spoken language translation. Our analysis shows that the system can successfully resolve 47% of the errors, resulting in a dramatic improvement in the transfer of problematic concepts.

2011

pdf bib
On-line Language Model Biasing for Statistical Machine Translation
Sankaranarayanan Ananthakrishnan | Rohit Prasad | Prem Natarajan
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

pdf bib
Source Error-Projection for Sample Selection in Phrase-Based SMT for Resource-Poor Languages
Sankaranarayanan Ananthakrishnan | Shiv Vitaladevuni | Rohit Prasad | Prem Natarajan
Proceedings of 5th International Joint Conference on Natural Language Processing

2010

pdf bib
A Semi-Supervised Batch-Mode Active Learning Strategy for Improved Statistical Machine Translation
Sankaranarayanan Ananthakrishnan | Rohit Prasad | David Stallard | Prem Natarajan
Proceedings of the Fourteenth Conference on Computational Natural Language Learning

pdf bib
Discriminative Sample Selection for Statistical Machine Translation
Sankaranarayanan Ananthakrishnan | Rohit Prasad | David Stallard | Prem Natarajan
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

2008

pdf bib
A Wearable Headset Speech-to-Speech Translation System
Kriste Krstovski | Michael Decerbo | Rohit Prasad | David Stallard | Shirin Saleem | Premkumar Natarajan
Proceedings of the ACL-08: HLT Workshop on Mobile Language Processing