speech recognition

In many modern applications such as directory assistance, name dialing, car navigation, etc. one needs a speech recognizer and/or a speech synthesizer. The former to recognize spoken user commands and the latter to pronounce information found in a database. Both components make use of phonetic transcriptions of the words to recognize/pronounce. In order to develop an application, the developer needs a tool that accepts words/sentences and that returns the phonetic transcriptions of these words/sentences.

This EU-FP7 project aims at investigating whether it is possible to incorporate principles of human brain processing (such as self-organization, deep hierarchical processes, fast adaptation, supervised and unsupervised learning) into a new type of automatic speech recognizer. We will attempt to reach our goal by adopting the paradigm of reservoir computing because it has been demonstrated recently that this paradigm allows one to build accurate and robust (against noise) isolated digit recognizers.

This STEVIN project is coordinated by TNO Utrecht and is about the setting up of a large-scale benchmark for speech recognition in Dutch, and with participation of different research groups in the Netherlands (Nijmegen, Twente, Delft), Flanders (Gent, Leuven) and abroad (TU-Brno and LIMSI)