Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Erik Edwards"'
Autor:
Ryan T Canolty, Maryam Soltani, Sarang S Dalal, Erik Edwards, Nina F Dronkers, Srikantan S Nagarajan, Heidi E Kirsch, Nicholas M Barbaro, Robert T Knight
Publikováno v:
Frontiers in Neuroscience, Vol 1 (2007)
We examined the spatiotemporal dynamics of word processing by recording the electrocorticogram (ECoG) from the lateral frontotemporal cortex of neurosurgical patients chronically implanted with subdural electrode grids. Subjects engaged in a target d
Externí odkaz:
https://doaj.org/article/a46c0663987642958bfd3b917b798196
Autor:
Eddie Hill, Chris A.B. Zajchowski, Abigail Rossiter, Erik Edwards, Mike Willett, Eleanor Crofford
Publikováno v:
College Student Affairs Journal. 41:46-57
Publikováno v:
Journal of Experiential Education. 44:328-345
Background: Smartphones provide limitless opportunity for communication and access to the world through social media, texting, and numerous applications. As their popularity continues to grow among college students, it is important to understand the
Publikováno v:
INTERSPEECH
Autor:
Abigail Rossiter, Eleanor Crofford, Erik Edwards, Eddie Hill, Chris A. B. Zajchowski, Michael Willett
Publikováno v:
Journal of Outdoor Recreation, Education, and Leadership. 12
Autor:
Maxim Korenevsky, Nico Axtmann, David Suendermann-Oeft, Najmeh Sadoughi, Michael Brenndoerfer, Amanda L. Robinson, Mark Miller, Erik Edwards, Greg P. Finley
Publikováno v:
Speech and Computer ISBN: 9783319995786
SPECOM
SPECOM
A synthetic corpus of dialogs was constructed from the LibriSpeech corpus, and is made freely available for diarization research. It includes over 90 h of training data, and over 9 h each of development and test data. Both 2-person and 3-person dialo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5f5be605c2eef975348aa12af96f39a
https://doi.org/10.1007/978-3-319-99579-3_13
https://doi.org/10.1007/978-3-319-99579-3_13
Autor:
David Suendermann-Oeft, Amanda L. Robinson, Mark Miller, Michael Brenndoerfer, Erik Edwards, Nico Axtmann, Greg P. Finley, Maxim Korenevsky, Najmeh Sadoughi
Publikováno v:
Speech and Computer ISBN: 9783319995786
SPECOM
SPECOM
A top-down approach to speaker diarization is developed using a modified Baum-Welch algorithm. The HMM states combine phonemes according to structural positions under syllabic phonological theory. By nature of the structural phonology, there are at m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75523d0ff686e577ecc913844294cbf2
https://doi.org/10.1007/978-3-319-99579-3_14
https://doi.org/10.1007/978-3-319-99579-3_14
Autor:
Nico Axtmann, Najmeh Sadoughi, Gregory Finley, Amanda L. Robinson, Mark Miller, Michael Brenndoerfer, Erik Edwards, David Suendermann-Oeft, Wael Salloum
Publikováno v:
NAACL-HLT (3)
A typical workflow to document clinical encounters entails dictating a summary, running speech recognition, and post-processing the resulting text into a formatted letter. Post-processing entails a host of transformations including punctuation restor
Autor:
Nico Axtmann, Maxim Korenevsky, Michael Brenndoerfer, Najmeh Sadoughi, David Suendermann-Oeft, Erik Edwards, Greg P. Finley, Wael Salloum, Amanda L. Robinson, Mark Miller
Publikováno v:
Speech and Computer ISBN: 9783319995786
SPECOM
SPECOM
Training models for speech recognition usually requires accurate word-level transcription of available speech data. For the domain of medical dictations, it is common to have “semi-literal” transcripts available: large numbers of speech files alo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b645588d32900fcea8dab1602591db28
https://doi.org/10.1007/978-3-319-99579-3_19
https://doi.org/10.1007/978-3-319-99579-3_19
Autor:
Amanda L. Robinson, Najmeh Sadoughi, Maxim Korenevsky, David Suendermann-Oeft, Mark Miller, Nico Axtmann, Greg P. Finley, Michael Brenndoerfer, Erik Edwards
Publikováno v:
Speech and Computer ISBN: 9783319995786
SPECOM
SPECOM
We present a section boundary detection framework specifically for clinical dictations. Detection is cast as a semi-supervised binary tagging problem and solved using a neural network model composed of a stack of embeddings, unidirectional long-short
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e4723470686e61838151e539fd8d800
https://doi.org/10.1007/978-3-319-99579-3_58
https://doi.org/10.1007/978-3-319-99579-3_58