The development of a high-performance telephone-bandwidth speaker independent connected digit recognizer for Italian is described. The CSLU Speech Toolkit was used to develop and implement the hybrid ANN/HMM system, which is trained on context-dependent categories to account for coarticulatory variation. Various front-end processing and system architectures were compared and, when the best features (MFCC with CMS + ?) and network (4-layer fully connected feed-forward network) were considered, there was a 98.92% word recognition accuracy and a 92.62% sentence recognition accuracy on a test set of the FIELD continuous digits recognition task.
Publication type:
Contributo in atti di convegno
Publisher:
IEEE, New York, USA
Source:
ASRU 2001 - Automatic Speech Recognition and Understanding Workshop, pp. 405–408, Madonna di Campiglio, Trento (Italy), December 9-13, 2001
Date:
2001
Resource Identifier:
http://www.cnr.it/prodotto/i/240877
https://dx.doi.org/10.1109/ASRU.2001.1034670
info:doi:10.1109/ASRU.2001.1034670
http://www2.pd.istc.cnr.it/Papers/PieroCosi/cp-ASRU2001.pdf
urn:isbn:0-7803-7343-X
Language:
Eng