Resynthesizing the GECO speech corpus with VocalTractLab

We are addressing the challenge of learning an inverse mapping between
acoustic features and control parameters of a vocal tract simulator. As a first step,
we synthesize an articulatory corpus consisting of control parameters and wave
forms using VocalTractLab (VTL; [1]) as the vocal tract simulator. The basis for
the synthesis is a concatenative approach that combines gestures of VTL according
to a SAMPA transcription. SAMPA transcriptions are taken from the GECO corpus
[2], a spontaneous speech corpus of southern German. The presented approach uses
the duration of the phones and extracted pitch contours to create gesture files for the
VTL. The resynthesis of the GECO corpus results in 53960 valid spliced out word
samples totalling in 6 hours and 23 minutes of synthesized speech. The synthesis
quality is mediocre. We believe that the synthesized samples resemble some of the
natural variability found in natural human speech.