Paper 2292
A Blueprint for a Comprehensive Australian English Auditory-Visual Speech Corpus
Denis Burnham, Eliathamby Ambikairajah, Joanne Arciuli, Mohammed Bennamoun, Catherine T. Best, Steven Bird, Andrew R. Butcher, Steve Cassidy, Girija Chetty, Felicity M. Cox, Anne Cutler, Robert Dale, Julien R. Epps, Janet M. Fletcher, Roland Goecke, David B. Grayden, John T. Hajek, John C. Ingram, Shunichi Ishihara, Nenagh Kemp, Yuko Kinoshita, Takaaki Kuratate, Trent W. Lewis, Debbie E. Loakes, Mark Onslow, David M. Powers, Philip Rose, Roberto Togneri, Dat Tran, and Michael Wagner
96-107 (complete paper or proceedings contents)
Abstract
Large auditory-visual (AV) speech corpora are the grist of modern research in speech science, but no such corpus exists for Australian English. This is unfortunate, for speech science is the brains behind speech technology and applications such as text-to-speech (TTS) synthesis, automatic speech recognition (ASR), speaker recognition and forensic identification, talking heads, and hearing prostheses. Advances in these research areas in Australia require a large corpus of Australian English. Here the authors describe a blueprint for building the Big Australian Speech Corpus (the Big ASC), a corpus of over 1,100 speakers from urban and rural Australia, including speakers of non-indigenous, indigenous, ethnocultural, and disordered forms of Australian English, each of whom would be sampled on three occasions in a range of speech tasks designed by the researchers who would be using the corpus.
Published in
Selected Proceedings of the 2008 HCSNet Workshop on Designing the Australian National Corpus: Mustering Languages
edited by Michael Haugh, Kate Burridge, Jean Mulder, and Pam Peters
Table of contents
Paper 2292
A Blueprint for a Comprehensive Australian English Auditory-Visual Speech Corpus
Denis Burnham, Eliathamby Ambikairajah, Joanne Arciuli, Mohammed Bennamoun, Catherine T. Best, Steven Bird, Andrew R. Butcher, Steve Cassidy, Girija Chetty, Felicity M. Cox, Anne Cutler, Robert Dale, Julien R. Epps, Janet M. Fletcher, Roland Goecke, David B. Grayden, John T. Hajek, John C. Ingram, Shunichi Ishihara, Nenagh Kemp, Yuko Kinoshita, Takaaki Kuratate, Trent W. Lewis, Debbie E. Loakes, Mark Onslow, David M. Powers, Philip Rose, Roberto Togneri, Dat Tran, and Michael Wagner
96-107 (complete paper or proceedings contents)
Denis Burnham, Eliathamby Ambikairajah, Joanne Arciuli, Mohammed Bennamoun, Catherine T. Best, Steven Bird, Andrew R. Butcher, Steve Cassidy, Girija Chetty, Felicity M. Cox, Anne Cutler, Robert Dale, Julien R. Epps, Janet M. Fletcher, Roland Goecke, David B. Grayden, John T. Hajek, John C. Ingram, Shunichi Ishihara, Nenagh Kemp, Yuko Kinoshita, Takaaki Kuratate, Trent W. Lewis, Debbie E. Loakes, Mark Onslow, David M. Powers, Philip Rose, Roberto Togneri, Dat Tran, and Michael Wagner
96-107 (complete paper or proceedings contents)
Abstract
Large auditory-visual (AV) speech corpora are the grist of modern research in speech science, but no such corpus exists for Australian English. This is unfortunate, for speech science is the brains behind speech technology and applications such as text-to-speech (TTS) synthesis, automatic speech recognition (ASR), speaker recognition and forensic identification, talking heads, and hearing prostheses. Advances in these research areas in Australia require a large corpus of Australian English. Here the authors describe a blueprint for building the Big Australian Speech Corpus (the Big ASC), a corpus of over 1,100 speakers from urban and rural Australia, including speakers of non-indigenous, indigenous, ethnocultural, and disordered forms of Australian English, each of whom would be sampled on three occasions in a range of speech tasks designed by the researchers who would be using the corpus.
Published in
Selected Proceedings of the 2008 HCSNet Workshop on Designing the Australian National Corpus: Mustering Languages
edited by Michael Haugh, Kate Burridge, Jean Mulder, and Pam Peters
Table of contents
edited by Michael Haugh, Kate Burridge, Jean Mulder, and Pam Peters
Table of contents