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-21057@www.clsp.jhu.edu DTSTAMP:20240329T114046Z CATEGORIES;LANGUAGE=en-US:Seminars CONTACT: DESCRIPTION:Abstract\nThis talk will outline the major challenging in porti ng mainstream speech technology to the domain of clinical applications\; i n particular\, the need for personalised systems\, the challenge of workin g in an inherently sparse data domain and developing meaningful collaborat ions with all stakeholders. The talk will give an overview of recent state -of-the-art research from current projects including in the areas of recog nition of disordered speech\, automatic processing of conversations and th e automatic detection and tracking of paralinguistic information at the Un iversity of Sheffield (UK)’s Speech and Hearing (SPandH) & Healthcare lab. \nBiography\nHeidi is a Senior Lecturer (associate professor) in Computer Science at the University of Sheffield\, United Kingdom. Her research inte rests are on the application of AI-based voice technologies to healthcare. In particular\, the detection and monitoring of people’s physical and men tal health including verbal and non-verbal traits for expressions of emoti on\, anxiety\, depression and neurodegenerative conditions in e.g.\, thera peutic or diagnostic settings. DTSTART;TZID=America/New_York:20211119T120000 DTEND;TZID=America/New_York:20211119T131500 LOCATION:Hackerman Hall B17 @ 3400 N. Charles Street\, Baltimore\, MD 21218 SEQUENCE:0 SUMMARY:Heidi Christensen (University of Sheffield\, UK) Virtual Seminar “A utomated Processing of Pathological Speech: Recent Work and Ongoing Challe nges” URL:https://www.clsp.jhu.edu/events/heidi-christensen-university-of-sheffie ld-uk-virtual-seminar-automated-processing-of-pathological-speech-recent-w ork-and-ongoing-challenges/ X-COST-TYPE:free X-ALT-DESC;FMTTYPE=text/html:\\n\\n
\\nAbstr act
\nThis talk will outline the major challenging in porti ng mainstream speech technology to the domain of clinical applications\; i n particular\, the need for personalised systems\, the challenge of workin g in an inherently sparse data domain and developing meaningful collaborat ions with all stakeholders. The talk will give an overview of recent state -of-the-art research from current projects including in the areas of recog nition of disordered speech\, automatic processing of conversations and th e automatic detection and tracking of paralinguistic information at the Un iversity of Sheffield (UK)’s Speech and Hearing (SPandH) & Healthcare lab.
\nBiography
\nHeidi is a Senior Lecturer (as sociate professor) in Computer Science at the University of Sheffield\, Un ited Kingdom. Her research interests are on the application of AI-based vo ice technologies to healthcare. In particular\, the detection and monitori ng of people’s physical and mental health including verbal and non-verbal traits for expressions of emotion\, anxiety\, depression and neurodegenera tive conditions in e.g.\, therapeutic or diagnostic settings.
\n X-TAGS;LANGUAGE=en-US:2021\,Christensen\,November END:VEVENT BEGIN:VEVENT UID:ai1ec-23513@www.clsp.jhu.edu DTSTAMP:20240329T114046Z 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\\nAbstr act
\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.
\nBiography
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