An Enhanced Electrolarynx with Automatic Fundamental Frequency Control based on Statistical Prediction

An electrolarynx is a type of speaking aid device which is able to mechanically generate excitation sounds to help laryngectomees produce electrolaryngeal (EL) speech. Although EL speech is quite intelligible, its naturalness suffers from monotonous fundamental frequency patterns of the mechanical excitation sounds. To make it possible to generate more natural excitation sounds, we have proposed a method to automatically control the fundamental frequency of the sounds generated by the electrolarynx based on a statistical prediction model, which predicts the fundamental frequency patterns from the produced EL speech in real-time. In this paper, we develop a prototype system by implementing the proposed control method in an actual, physical electrolarynx and evaluate its performance.