BEGIN:VCALENDAR VERSION:2.0 PRODID:-//128.220.36.25//NONSGML kigkonsult.se iCalcreator 2.26.9// CALSCALE:GREGORIAN METHOD:PUBLISH X-FROM-URL:https://www.clsp.jhu.edu X-WR-TIMEZONE:America/New_York BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:STANDARD DTSTART:20231105T020000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RDATE:20241103T020000 TZNAME:EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20240310T020000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RDATE:20250309T020000 TZNAME:EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:ai1ec-23513@www.clsp.jhu.edu DTSTAMP:20240329T112818Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:Abstract\nDespite many recent advances in automatic speech reco gnition (ASR)\, linguists and language communities engaged in language doc umentation projects continue to face the obstacle of the “transcription bo ttleneck”. Researchers in NLP typically do not distinguish between widely spoken languages that currently happen to have few training resources and endangered languages that will never have abundant data. As a result\, we often fail to thoroughly explore when ASR is helpful for language document ation\, what architectures work best for the sorts of languages that are i n need of documentation\, and how data can be collected and organized to p roduce optimal results. In this talk I describe several projects that atte mpt to bridge the gap between the promise of ASR for language documentatio n and the reality of using this technology in real-world settings.\nBiogra phy\nEmily Prud’hommeaux is the Gianinno Family Sesquicentennial Assistant Professor in the Department of Computer Science at Boston College. She re ceived her BA (Harvard) and MA (University of California\, Los Angeles) in Linguistics\, and her PhD in Computer Science and Engineering (OHSU/OGI). Her research area is natural language processing in low-resource settings \, with a particular focus on endangered languages and the language of ind ividuals with conditions impacting communication and cognition. DTSTART;TZID=America/New_York:20230331T120000 DTEND;TZID=America/New_York:20230331T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD 21218 SEQUENCE:0 SUMMARY:Emily Prud’hommeaux (Boston College) “Endangered or Just Under-Reso urced? Evaluating ASR Quality and Utility When Data is Scarce” URL:https://www.clsp.jhu.edu/events/emily-prudhommeaux-boston-college/ X-COST-TYPE:free X-ALT-DESC;FMTTYPE=text/html:\\n\\n
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\nDespite many recent advances in automatic speech reco gnition (ASR)\, linguists and language communities engaged in language doc umentation projects continue to face the obstacle of the “transcription bo ttleneck”. Researchers in NLP typically do not distinguish between widely spoken languages that currently happen to have few training resources and endangered languages that will never have abundant data. As a result\, we often fail to thoroughly explore when ASR is helpful for language document ation\, what architectures work best for the sorts of languages that are i n need of documentation\, and how data can be collected and organized to p roduce optimal results. In this talk I describe several projects that atte mpt to bridge the gap between the promise of ASR for language documentatio n and the reality of using this technology in real-world settings.
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