Italian Children's Speech Recognition for Advanced Interactive Literacy Tutors

This work was conducted with the specific goals of developing improved recognition of children's speech in Italian and the integration of the children's speech recognition models into the Italian version of the Colorado Literacy Tutor platform. Specifically, children's speech recognition research for Italian was conducted using the ITC-irst Children's Speech Corpus. Using the University of Colorado SONIC LVSR system, we demonstrate a phonetic recognition error rate of 16.0% for a system which incorporates Vocal Tract Length Normalization (VTLN), Speaker-Adaptive Trained phonetic models, as well as unsupervised Structural MAP Linear Regression (SMAPLR). These new acoustic models have been incorporated within an Italian version of SONIC the ASR system of the Italian Literacy Tutor program.