Advances in Large Vocabulary Continuous Speech Recognition in Greek: Modeling and nonlinear features

摘要

The main goal of this work is the development of an improved Large Vocabulary Continuous Speech Recognition (LVCSR) framework in Greek. Language modeling is carried out in a collection of journalistic text and in the acoustic signal processing, a nonlinear approach is implemented for deriving features of the AM-FM type. Experimentation is carried out in both clean and simulated far-field speech offering insight about the acoustic modeling under adverse conditions with reverberation and additive ambient noise. Beyond the baseline implementation, a first step is made in exploring how standard (MFCCs and PLPs) and modulation features (AM-FM) behave in a LVCSR framework when the input speech is distant, like in real life home applications.