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We’ve managed to make this paper open access, so I thought I would share it with Assistech. It describes a new type of VOCA that uses speech recognition as an input. Please pass on the link as you see fit.
Following on from the research reported in the paper, we’ve produced a better version on dedicated hardware and will be trialling this new version in the next few months
Best wishes
Mark
Click on this link to get the pdf http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06259889
This paper appears in:
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Date of Publication: Jan. 2013
Author(s): Hawley,
M.S.
M. Hawley is
with the School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK.(email:mark.hawley@sheffield.ac.uk)
Cunningham, S.P. ; Green,
P.D. ; Enderby,
P. ; Palmer,
R. ; Sehgal, S. ; O'Neill,
P.
Volume: 21 , Issue:
1
Page(s): 23 - 31
Product Type: Journals & Magazines
A new form of augmentative and alternative communication (AAC) device for people with severe speech impairment-the voice-input voice-output communication aid (VIVOCA)-is described. The VIVOCA recognizes the disordered speech of the user and builds messages, which are converted into synthetic speech. System development was carried out employing user-centered design and development methods, which identified and refined key requirements for the device. A novel methodology for building small vocabulary, speaker-dependent automatic speech recognizers with reduced amounts of training data, was applied. Experiments showed that this method is successful in generating good recognition performance (mean accuracy 96%) on highly disordered speech, even when recognition perplexity is increased. The selected message-building technique traded off various factors including speed of message construction and range of available message outputs. The VIVOCA was evaluated in a field trial by individuals with moderate to severe dysarthria and confirmed that they can make use of the device to produce intelligible speech output from disordered speech input. The trial highlighted some issues which limit the performance and usability of the device when applied in real usage situations, with mean recognition accuracy of 67% in these circumstances. These limitations will be addressed in future work.