Priscilla Kan John
An Automatic Vowel Space Generator for Language Learner Pronunciation Acquisition and Correction
Xinyuan Chao | Charbel El-Khaissi | Nicholas Kuo | Priscilla Kan John | Hanna Suominen
Proceedings of the The 18th Annual Workshop of the Australasian Language Technology Association
Speech visualisations are known to help language learners to acquire correct pronunciation and promote a better study experience. We present a two-step approach based on two established techniques to display tongue tip movements of an acoustic speech signal on a vowel space plot. First we use Energy Entropy Ratio to extract vowels; and then we apply Linear Predictive Coding root method to estimate Formant 1 and Formant 2. We invited and collected acoustic data from one Modern Standard Arabic (MSA) lecture and four MSA students. Our proof of concept was able to reflect differences between the tongue tip movements in a native MSA speaker to those of a MSA language learner. This paper addresses principle methods for generating features that reflect bio-physiological features of speech and thus, facilitates an approach that can be generally adapted to languages other than MSA.