Frame-based acoustic feature integration for speech understanding

With the purpose of improving Spoken Language Understanding (SLU) performance, a combination of different acoustic speech recognition (ASR) systems is proposed. State a-posteriori probabilities obtained with systems using different acoustic feature sets are combined with log-linear interpolation. In order to perform a coherent combination of these probabilities, acoustic models must have the same topology (i.e. same set of states). For this purpose, a fast and efficient twin model training protocol is proposed. By a wise choice of acoustic feature sets and log-linear interpolation of their likelihood ratios, a substantial Concept Error Rate (CER) reduction has been observed on the test part of the French MEDIA corpus.

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Loic Barrault, Christophe Servan, Driss Matrouf, Georges Linares, Renato de Mori
• Keywords: Acoustic Feature Sets, ICASSP 2008, Log-linear Interpolation, Signal Processing, State A-posteriori Probabilities