The development of a speaker independent "general purpose" phonetic recognizer for Italian is described. The CSLU Toolkit was used to develop and implement the system. The recognizer, based on a frame-based hybrid HMM/ANN architecture trained on context-dependent categories to account for coarticulatory variation, recognizes 38 different phonemes (not including silence or closures), and can distinguish between stressed and unstressed vowels as well as open and closed vowels. The APASCI corpus, containing nearly 2500 sentences read by 100 speakers, where the sentences have been designed to maximize the number of phonemes occurring in different contexts, was used for training and testing. As of the time of this writing, a phoneme-level accuracy of 82.90% on the development set and of 80.53% on the test set has been obtained. This level of accuracy is much greater than on a similar English-language corpus (with state-of-the-art performance of slightly better than 70%) and it represents the best performance obtained so far on this corpus.
High Performance "General Purpose" Phonetic Recognition for Italian
Cosi P;
2000
Abstract
The development of a speaker independent "general purpose" phonetic recognizer for Italian is described. The CSLU Toolkit was used to develop and implement the system. The recognizer, based on a frame-based hybrid HMM/ANN architecture trained on context-dependent categories to account for coarticulatory variation, recognizes 38 different phonemes (not including silence or closures), and can distinguish between stressed and unstressed vowels as well as open and closed vowels. The APASCI corpus, containing nearly 2500 sentences read by 100 speakers, where the sentences have been designed to maximize the number of phonemes occurring in different contexts, was used for training and testing. As of the time of this writing, a phoneme-level accuracy of 82.90% on the development set and of 80.53% on the test set has been obtained. This level of accuracy is much greater than on a similar English-language corpus (with state-of-the-art performance of slightly better than 70%) and it represents the best performance obtained so far on this corpus.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
