@techreport{TD:101116,
	att_abstract={{Simultaneous translation is the challenging task of listening to source language speech, and at the same time, producing target language speech. Human interpreters achieve this task routinely and effortlessly, using different strategies in order to minimize the latency in producing target language. Toward modeling the human interpretation process, we compare and contrast three incremental decoding and two different input segmentation strategies for simultaneous translation in this paper. We present accuracy and latency tradeoffs for each of the decoding strategies when applied to audio lectures from the TED collection.}},
	att_authors={vk947h, sb7658},
	att_categories={},
	att_copyright={{Association of Computational Linguistics}},
	att_copyright_notice={{The definitive version was published in   2013. {{, 2013-11-04}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:101116},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:101116_DS1_2013-07-11T18:10:38.794Z.pdf},
	author={Vivek kumar Rangarajan sridhar and Srinivas Bangalore and Mahsa Yarmohammadi and Baskaran Sankaran},
	institution={{IJCNLP}},
	month={November},
	title={{Incremental Segmentation and Decoding Strategies for Simultaneous Translation}},
	year=2013,
}