Representation Of Vocal Tract Research Articles

Vocal Tract Images Reveal Neural Representations of Sensorimotor Transformation During Speech Imitation.

Imitating speech necessitates the transformation from sensory targets to vocal tract motor output, yet little is known about the representational basis of this process in the human brain. Here, we address this question by using real-time MR imaging (rtMRI) of the vocal tract and functional MRI (fMRI) of the brain in a speech imitation paradigm. Participants trained on imitating a native vowel and a similar nonnative vowel that required lip rounding. Later, participants imitated these vowels and an untrained vowel pair during separate fMRI and rtMRI runs. Univariate fMRI analyses revealed that regions including left inferior frontal gyrus were more active during sensorimotor transformation (ST) and production of nonnative vowels, compared with native vowels; further, ST for nonnative vowels activated somatomotor cortex bilaterally, compared with ST of native vowels. Using test representational similarity analysis (RSA) models constructed from participants’ vocal tract images and from stimulus formant distances, we found that RSA searchlight analyses of fMRI data showed either type of model could be represented in somatomotor, temporal, cerebellar, and hippocampal neural activation patterns during ST. We thus provide the first evidence of widespread and robust cortical and subcortical neural representation of vocal tract and/or formant parameters, during prearticulatory ST.

Realtime and accurate musical control of expression in singing synthesis

In this paper, we describe a full computer-based musical instrument allowing realtime synthesis of expressive singing voice. The expression results from the continuous action of an interpreter through a gestural control interface. In this context, expressive features of voice are discussed. New real-time implementations of a spectral model of glottal flow (CALM) are described. These interactive modules are then used to identify and quantify voice quality dimensions. Experiments are conducted in order to develop a first framework for voice quality control. The representation of vocal tract and the control of several vocal tract movements are explained and a solution is proposed and integrated. Finally, some typical controllers are connected to the system and expressivity is evaluated.