Abstract

In speech production research, the integration of articulatory data derived from multiple measurement modalities can provide rich description of vocal tract dynamics by overcoming the limited spatio-temporal representations offered by individual modalities. This paper presents a spatial and temporal alignment method between two promising modalities using a corpus of TIMIT sentences obtained from the same speaker: flesh point tracking from Electromagnetic Articulography (EMA) that offers high temporal resolution but sparse spatial information and real time Magnetic Resonance Imaging (MRI) that offers good spatial details but at lower temporal rates. Spatial alignment is done by using palate tracking of EMA, but distortion in MRI audio and articulatory data variability make temporal alignment challenging. This paper proposes a novel alignment technique using joint acoustic-articulatory features which combines …

Date

2013

Authors

Jangwon Kim, Adam Lammert, Prasanta Ghosh, Shrikanth S Narayanan

Conference

2013 IEEE International Conference on Acoustics, Speech and Signal Processing

Pages

3637-3641

Publisher

IEEE