Development of an articulatory visual-speech synthesizer to support language learning

Abstract

This paper presents a two-dimensional (2D) visual-speech synthesizer to support language learning. A visual-speech synthesizer animates the human articulators in synchronization with speech signals, e.g., output from a text-to-speech synthesizer. A visual-speech animation can offer a concrete illustration to the language learners on how to move and where to place the articulators when pronouncing a phoneme. We adopt a 2D vector-based viseme models and compiled a collection of visemes to cover the articulation of all English phonemes (42 visemes for the 44 English phonemes). Morphing between properly selected vector-based articulation images achieves articulatory animations. In this way, we have developed an articulatory visual speech synthesizer that can accept free-text input and synthesize articulatory dynamics in real-time. Evaluation involving 32 subjects based on “lip-reading” shows that they can identify the appropriate word(s) based on articulation animation alone nearly ∼80% of the time