French GlobalPhone Database

This report presents one month trainee work on development of French Automatic Speech Recogni-tion (ASR) system using a french part of multilingual database GlobalPhone FR. The purpose of this report is to explain and give results of the training and testing of the ASR with this specific database. Two different methods are presented, the Hidden Markov Model (HMM) with MFCC/PLP features and tandem features from Multilayer Perceptron (MLP) phone posteriors. The report presents data prepara-tion for GlobalPhone FR ASR training, and compares the two different approaches. Word recognition accuracy achieved with MFCC features is 71.46 % and the tandem features with 3-layer MLP improved the accuracy to 72.15%. We interpret this result as a baseline for the GlobalPhone FR database