AwezaMed automatic speech recognition (ASR) test data
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dc.contact.email | KCalteaux@csir.co.za | en_ZA |
dc.contact.name | Karen Calteaux | en_ZA |
dc.contributor.author | Bandehorst, Jaco | |
dc.contributor.other | Van Niekerk, Nina | |
dc.contributor.other | Calteaux, Karen | |
dc.date.accessioned | 2025-02-12T11:12:33Z | |
dc.date.available | 2025-02-12T11:12:33Z | |
dc.date.issued | 2020-12 | |
dc.description | The corpus contains orthographically transcribed broadband speech in four official languages of South Africa: Afrikaans, English, isiXhosa and isiZulu. Respondents read a number of ASR prompts (10 or 20) in a real-world environment. Dataset includes 1 hour of test data | en_ZA |
dc.identifier.uri | https://hdl.handle.net/20.500.12185/688 | |
dc.languages | Afrikaans | en_ZA |
dc.languages | English | en_ZA |
dc.languages | isiXhosa | en_ZA |
dc.languages | isiZulu | en_ZA |
dc.media.category | Annotated Speech Corpus | en_ZA |
dc.publisher | Voice Computing (VC) Research Group at the CSIR Nextgen Enterprises and Institutions (NGEI) | en_ZA |
dc.rights.license | Creative Commons Attribution 3.0 Unported (CC BY 3.0): https://creativecommons.org/licenses/by/3.0/legalcode | en_ZA |
dc.subject | ASR | en_ZA |
dc.subject | Test data | en_ZA |
dc.subject | Speech corpora | en_ZA |
dc.subject | AwezaMed | en_ZA |
dc.title | AwezaMed automatic speech recognition (ASR) test data | en_ZA |
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