{"id":2201,"date":"2005-01-15T23:40:30","date_gmt":"2005-01-16T04:40:30","guid":{"rendered":"https:\/\/engineering.jhu.edu\/magazine-archive\/?p=2201"},"modified":"2014-12-15T23:41:41","modified_gmt":"2014-12-16T04:41:41","slug":"bumper-crop-research-language-engineering","status":"publish","type":"post","link":"https:\/\/engineering.jhu.edu\/magazine-archive\/2005\/01\/bumper-crop-research-language-engineering\/","title":{"rendered":"A Bumper Crop of Research in Language Engineering"},"content":{"rendered":"
\"Undergraduates<\/a>
Undergraduates David W. Kirsch (left) of Lehigh University and Philip Bramsen of MIT worked together on techniques to improve computer recognition of accented speech, one of the three team projects at the Center for Language and Speech Processing (CLSP) Summer Workshop on Language Engineering.<\/strong><\/figcaption><\/figure>\n

\u201cRecognize Speech vs. Wreck a Nice Beach.\u201d That phrase, part of a lecture title, sums up the enormous challenge of automatic speech recognition. To decipher the subtleties of language, computers must sift through accents, grammatical errors, ambient noise, and language oddities. Pair or pear? Sex or sects? Ta-may-toe or toe-mah-toe? Even more of a digital puzzle is programming a search engine to find an image of a juicy, ripe Big Boy if the image isn\u2019t labeled \u201ctomato.\u201d<\/p>\n

For 10 years, the Whiting School of Engineering\u2019s Center for Language and Speech Processing (CLSP) Summer Workshop on Language Engineering has been pairing senior researchers from academia and industry with top students to address just those kinds of challenges. Their mission is to advance the field in the areas of speech recognition, trans-lingual information detection and extraction, machine translation, speech synthesis, information retrieval, topic detection and tracking, text summarization, and question answering.<\/p>\n

For the 2004 workshop\u2019s 37 participants, this 10th anniversary milestone most likely passed with little fanfare. Instead, it was business as usual as they worked together in Schaffer Hall\u2019s computer labs\u2014often late into the night\u2014to find cutting-edge solutions.<\/p>\n

The workshop \u201chas become the program for which the CLSP is famous,\u201d says Frederick R. Jelinek, the Center\u2019s director and the Julian Sinclair Smith Professor in the Department of Electrical and Computer Engineering. When he joined the Center in 1993, he saw an opportunity to bring its holistic approach to a six-week, intensive summer research experience. \u201cMy idea was to develop teams working together on a few projects,\u201d Jelinek explains.<\/p>\n

Other workshops existed but did not involve such teams. CLSP inaugurated the summer workshop with funding from the Department of Defense. The National Science Foundation began support in 1998.<\/p>\n

\u201cThink of the workshop as the first feasibility studies for the field,\u201d Jelinek says. \u201cThere are various things developed here that will be used by the field forever.\u201d Contributions include data sets available to industry and academia via the CLSP web site (www.clsp.jhu.edu<\/strong>), numerous journal articles, conference presentations, and technological advances. The creation of Gazelle software for machine translation of natural languages was the 1999 workshop project led by Kevin Knight, senior research scientist at the Information Sciences Institute at the University of Southern California. \u201cThe main goal was to build a generic tool that the whole research community could use,\u201d says Knight. \u201cToday, all kinds of research groups are using Gazelle in their translation projects. It\u2019s become a staple in the field.\u201d<\/p>\n

The research community also values highly the two-week pre-workshop training session to bring undergraduates up-to-speed in language engineering. \u201cIt is considered so good that the Association for Computational Linguistics sends 10 students,\u201d says Jelinek.<\/p>\n

\"\u201cThere<\/a>
\u201cThere are various things developed here that will be used by the field forever,\u201d notes Frederick R. Jelinek, director of CLSP and the Julian Sinclair Smith Professor in Electrical and Computer Engineering in the Whiting School.<\/strong><\/figcaption><\/figure>\n

To develop its workshop projects, CLSP sponsors an annual fall proposal submission and two-day presentation process at Hopkins. After two to four topics are chosen, each team leader selects approximately seven team members, including senior researchers, three graduate students (at least one from Hopkins), and two undergraduates. The undergraduate component was added in 1998; these students are chosen via a national search.<\/p>\n

This past summer\u2019s workshop featured three projects. One team focused on developing a general framework to model phonetic, lexical, and pronunciation variability in dialectal Chinese automatic speech recognition. The project leader was Richard W. Sproat, professor of linguistics and of electrical and computer engineering at the University of Illinois at Urbana-Champaign (UIUC). Sproat\u2019s team explored techniques for improving recognition of accented speech by using a standard Chinese recognizer as a baseline system to study Shanghainese, the street dialect in China\u2019s largest city.<\/p>\n

Team member David W. Kirsch, a double major in computer science and cognitive science at Lehigh University, was one of the six undergraduates last summer. \u201cThis workshop was the first time since I started college that I really felt academically at home,\u201d says Kirsch. \u201cI was with the people I was supposed to be with and doing the work I was supposed to be doing.\u201d<\/p>\n

Kirsch, who now intends to pursue doctoral studies in computational linguistics and plans to apply to Hopkins, is continuing his workshop research. \u201cSome algorithms had occurred to me during the last two weeks of the workshop,\u201d he says. \u201cWe never got time to test them, so I presented my idea of finding a way to classify accents on a sliding scale.\u201d The workshop is funding his year-long research through the $100,000 it awards competitively each year, distributed among two to four undergraduate and graduate student participants.<\/p>\n

\"Giri<\/a>
Giri Iyengar, from the IBM T.J. Watson Research Center, led the workshop\u2019s project team on joint visual text models, which explored image-driven web searches.<\/strong><\/figcaption><\/figure>\n

The second workshop project last summer examined landmark-based speech recognition. By bringing together new ideas in linguistics, especially nonlinear phonology, with recent advances in artificial intelligence, the team explored how better to match human speech recognition performance. Mark Hasegawa-Johnson, assistant professor of electrical and computer engineering at UIUC, led the team. The technological goal was to create a model that would identify acoustic phonetic landmarks (the minimal elements that one needs to insert into a sound to make it intelligible) and piece them together to recognize words.<\/p>\n

The third project, joint visual text models, took computer recognition of words and speech to the next step: recognizing objects and images. Giri Iyengar of the IBM T.J. Watson Research Center led the team. \u201cWe\u2019re making inroads into a problem that has defied us for decades,\u201d observes Sanjeev Khudanpur, assistant professor of Electrical and Computer Engineering and a member of CLSP (the \u201cRecognize Speech vs. Wreck a Nice Beach\u201d title was from his workshop lecture in 2001). Current search engines can only look at how an image is named. This technology would enable image-driven web searches. \u201cWhile none of the algorithms is perfect, retrieval is much better,\u201d says Khudanpur. \u201cThis is very far into the future, but the tool also could have national security implications by searching on names and faces.<\/p>\n

\u201cAll research is gambling,\u201d adds Khudanpur, who first participated in the workshop as a graduate student in 1995 and now lends his expertise as a senior adviser. \u201cYou put ideas in and see what comes up and hope for the big pay-off. The sure bet of the workshop is to bring good people together who will continue to collaborate. It creates a lot of understanding.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

\u201cRecognize Speech vs. Wreck a Nice Beach.\u201d That phrase, part of a lecture title, sums up the enormous challenge of automatic speech recognition. To decipher the subtleties of language, computers must sift through accents, grammatical errors, ambient noise, and language oddities. Pair or pear? Sex or sects? Ta-may-toe or toe-mah-toe? Even more of a digital…<\/p>\n","protected":false},"author":4,"featured_media":2202,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[28],"tags":[],"class_list":["post-2201","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-features","issue-winter-2005"],"acf":[],"yoast_head":"\nA Bumper Crop of Research in Language Engineering - JHU Engineering Magazine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/magazine-archive\/2005\/01\/bumper-crop-research-language-engineering\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A Bumper Crop of Research in Language Engineering - JHU Engineering Magazine\" \/>\n<meta property=\"og:description\" content=\"\u201cRecognize Speech vs. Wreck a Nice Beach.\u201d That phrase, part of a lecture title, sums up the enormous challenge of automatic speech recognition. 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