Using Silence MR Image to Synthesise Dynamic MRI Vocal Tract Data of CV

• DOI: 10.21437/interspeech.2020-1173
• Publication Date: 2020-10-27T09:22:11Z
• Authors: Ioannis K. Douros; Ajinkya Kulkarni; Chrysanthi Dourou; Yu Xie; Jacques Felblinger; Karyna Isaieva; Pierre-André Vuissoz; Yves Laprie
• Keywords: image transformation; 03 medical and health sciences; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing; vocal tract; Speech resources enrichment; 0305 other medical science; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; rtMRI data; pseudo rtMRI synthesis

In this work we present an algorithm for synthesising pseudo rtMRI data of the vocal tract. rtMRI data on the midsagittal plane were used to synthesise target consonant-vowel (CV) using only a silence frame of the target speaker. For this purpose, several single speaker models were created. The input of the algorithm is a silence frame of both train and target speaker and the rtMRI data of the target CV. An image transformation is computed from each CV frame to the next one, creating a set of transformations that describe the dynamics of the CV production. Another image transformation is computed from the silence frame of train speaker to the silence frame of the target speaker and is used to adapt the set of transformations computed previously to the target speaker. The adapted set of transformations is applied to the silence of the target speaker tosynthesise his/her CV pseudo rtMRI data. Synthesised images from multiple single speaker models are frame aligned and then averaged to create the final version of synthesised images. Synthesised images are compared with the original ones using image cross-correlation. Results show good agreement between the synthesised and the original images.