The development of a speaker independent connected ¡°digits¡± recognizer for Italian is described. The CSLU Speech Toolkit was used to develop and implement the system which is based on an hybrid ANN/HMM architecture. The recognizer is trained on contextdependent categories to account for coarticulatory variation. Various front-end processing was compared and, when the best features (MFCC with CMS + Δ) were considered, there was a 98.68% word recognition accuracy (90.76% sentence recognition accuracy) on a test set of the FIELD continuous digits recognition task.
Cite as: Cosi, P., Hosom, J.-P., Tesser, F. (2000) High performance Italian continuous "digit" recognition. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 4, 242-245
@inproceedings{cosi00b_icslp, author={Piero Cosi and John-Paul Hosom and Fabio Tesser}, title={{High performance Italian continuous "digit" recognition}}, year=2000, booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)}, pages={vol. 4, 242-245} }