Baskaran Sankaran

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In this paper, we propose a novel finetuning algorithm for the recently introduced multiway, multilingual neural machine translate that enables zero-resource machine translation. When used together with novel manyto-one translation strategies, we empirically show that this finetuning algorithm allows the multi-way, multilingual model to translate a(More)
In this paper, we enhance the attention-based neural machine translation (NMT) by adding explicit coverage embedding models to alleviate issues of repeating and dropping translations in NMT. For each source word, our model starts with a full coverage embedding vector to track the coverage status, and then keeps updating it with neural networks as the(More)
Statistical machine translation is often faced with the problem of combining training data from many diverse sources into a single translation model which then has to translate sentences in a new domain. We propose a novel approach, ensemble decoding, which combines a number of translation systems dynamically at the decoding step. In this paper, we evaluate(More)
Attention-based Neural Machine Translation (NMT) models suffer from attention deficiency issues as has been observed in recent research. We propose a novel mechanism to address some of these limitations and improve the NMT attention. Specifically, our approach memorizes the alignments temporally (within each sentence) and modulates the attention with the(More)
We present a universal Parts-of-Speech (POS) tagset framework covering most of the Indian languages (ILs) following the hierarchical and decomposable tagset schema. In spite of significant number of speakers, there is no workable POS tagset and tagger for most ILs, which serve as fundamental building blocks for NLP research. Existing IL POS tagsets are(More)
This paper describes Kriya – a new statistical machine translation (SMT) system that uses hierarchical phrases, whichwere first introduced in the Hieromachine translation system (Chiang, 2007). Kriya supports both a grammar extraction module for synchronous context-free grammars (SCFGs) and a CKY-based decoder. There are several re-implementations of Hiero(More)
Although it has been always thought that Word Sense Disambiguation (WSD) can be useful for Machine Translation, only recently efforts have been made towards integrating both tasks to prove that this assumption is valid, particularly for Statistical Machine Translation (SMT). While different approaches have been proposed and results started to converge in a(More)
Research in Parts-of-Speech (POS) tagset design for European and East Asian languages started with a mere listing of important morphosyntactic features in one language and has matured in later years towards hierarchical tagsets, decomposable tags, common framework for multiple languages (EAGLES) etc. Several tagsets have been developed in these languages(More)
Statistical Machine Translation (SMT) is currently used in real-time and commercial settings to quickly produce initial translations for a document which can later be edited by a human. The SMT models specialized for one domain often perform poorly when applied to other domains. The typical assumption that both training and testing data are drawn from the(More)