Please use this identifier to cite or link to this item:
https://doi.org/10.21256/zhaw-27071
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hürlimann, Manuela | - |
dc.contributor.author | Galbier, Jolanda | - |
dc.contributor.author | Cieliebak, Mark | - |
dc.date.accessioned | 2023-02-17T10:19:19Z | - |
dc.date.available | 2023-02-17T10:19:19Z | - |
dc.date.issued | 2022-07-05 | - |
dc.identifier.issn | 0926-4981 | de_CH |
dc.identifier.issn | 1564-0094 | de_CH |
dc.identifier.uri | https://ercim-news.ercim.eu/en130/special/speech-to-text-technology-for-hard-of-hearing-people | de_CH |
dc.identifier.uri | https://digitalcollection.zhaw.ch/handle/11475/27071 | - |
dc.description.abstract | Hard-of-hearing people face challenges in daily interactions that involve spoken language, such as meetings or doctor’s visits. Automatic speech recognition technology can support them by providing a written transcript of the conversation. Pro Audito Schweiz, the Swiss federation of hard-of-hearing people, and the Centre for Artificial Intelligence (CAI) at the Zurich University of Applied Sciences (ZHAW) conducted a preliminary study into the use of Speech-to-Text (STT) for this target group. Our survey among the members of Pro Audito found that there is large interest in using automated solutions for better understanding in everyday situations. We now propose to take the next step and develop an application which uses ZHAW’s high-quality STT models. | de_CH |
dc.language.iso | en | de_CH |
dc.publisher | European Research Consortium for Informatics and Mathematics | de_CH |
dc.relation.ispartof | ERCIM News | de_CH |
dc.rights | https://creativecommons.org/licenses/by/4.0/ | de_CH |
dc.subject | Natural language processing | de_CH |
dc.subject | Speech-to-text | de_CH |
dc.subject | Accessibility | de_CH |
dc.subject | Schwerhörigkeit | de_CH |
dc.subject.ddc | 410.285: Computerlinguistik | de_CH |
dc.title | Speech-to-text technology for hard-of-hearing people | de_CH |
dc.type | Beitrag in Magazin oder Zeitung | de_CH |
dcterms.type | Text | de_CH |
zhaw.departement | School of Engineering | de_CH |
zhaw.organisationalunit | Centre for Artificial Intelligence (CAI) | de_CH |
dc.identifier.doi | 10.21256/zhaw-27071 | - |
zhaw.funding.eu | No | de_CH |
zhaw.issue | 130 | de_CH |
zhaw.originated.zhaw | Yes | de_CH |
zhaw.pages.end | 16 | de_CH |
zhaw.pages.start | 15 | de_CH |
zhaw.publication.status | publishedVersion | de_CH |
zhaw.webfeed | Datalab | de_CH |
zhaw.webfeed | Natural Language Processing | de_CH |
zhaw.webfeed | ZHAW digital | de_CH |
zhaw.author.additional | No | de_CH |
zhaw.display.portrait | Yes | de_CH |
Appears in collections: | Publikationen School of Engineering |
Files in This Item:
File | Description | Size | Format | |
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2022_Huerlimann-etal_Speech-to-text-technology-hard-of-hearing-people_ERCIM.pdf | 319.85 kB | Adobe PDF | View/Open |
Show simple item record
Hürlimann, M., Galbier, J., & Cieliebak, M. (2022). Speech-to-text technology for hard-of-hearing people. ERCIM News, 130, 15–16. https://doi.org/10.21256/zhaw-27071
Hürlimann, M., Galbier, J. and Cieliebak, M. (2022) ‘Speech-to-text technology for hard-of-hearing people’, ERCIM News, (130), pp. 15–16. Available at: https://doi.org/10.21256/zhaw-27071.
M. Hürlimann, J. Galbier, and M. Cieliebak, “Speech-to-text technology for hard-of-hearing people,” ERCIM News, no. 130, pp. 15–16, Jul. 2022, doi: 10.21256/zhaw-27071.
HÜRLIMANN, Manuela, Jolanda GALBIER und Mark CIELIEBAK, 2022. Speech-to-text technology for hard-of-hearing people. ERCIM News [online]. 5 Juli 2022. Nr. 130, S. 15–16. DOI 10.21256/zhaw-27071. Verfügbar unter: https://ercim-news.ercim.eu/en130/special/speech-to-text-technology-for-hard-of-hearing-people
Hürlimann, Manuela, Jolanda Galbier, and Mark Cieliebak. 2022. “Speech-to-Text Technology for Hard-of-Hearing People.” ERCIM News, no. 130 (July): 15–16. https://doi.org/10.21256/zhaw-27071.
Hürlimann, Manuela, et al. “Speech-to-Text Technology for Hard-of-Hearing People.” ERCIM News, no. 130, July 2022, pp. 15–16, https://doi.org/10.21256/zhaw-27071.
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