Learning an artificial F0-contour for ALT speech
Anna Katharina Fuchs, Martín Hagmüller · 2012
The Artificial Larynx Transducer (ALT) as a possibility to re-obtain audible speech for people who had to un-dergo a total laryngectomy has been known for decades. Not only the design and underlying technique but also the poor speech quality and intelligibility have not improved until now. In a world where technology rules everyday life, it is necessary to use the known technology to im-prove the quality of life for handicapped people. One reason for the lack of naturalness is the constant vibration of the ALT. A method to substantially improve ALT speech is to introduce a varying fundamental fre-quency (F0)- contour. In this paper we present a new method to automatically learn an artificial F0-contour. The model used is a Gaussian mixture model (GMM) which is trained with a database containing speech of ALT users as well as healthy people. Informal listening tests suggest that this approach is a first step for a sub-sequent overall enhancement technique for speech pro-duced by an ALT. Index Terms: alaryngeal speech, Artificial Larynx Transducer (ALT), fundamental frequency, speech en-