Although much is known about how speech is produced, and research into speech
production has resulted in measured articulatory data, feature systems of different kinds, and …

In this paper, we describe a statistical approach to both an articulatory-to-acoustic mapping
and an acoustic-to-articulatory inversion mapping without using phonetic information. The …

Continuous latent variable models (cLVMs) are probabilistic models that represent a
distribution in a high-dimensional Euclidean space using a small number of continuous …

The many-to-one mapping from representations in the speech articulatory space to acoustic
space renders the associated acoustic-to-articulatory inverse mapping non-unique. Among …

Estimating articulatory movements from speech acoustic features is known as acoustic-to-
articulatory inversion (AAI). Large amount of parallel data from speech and articulatory …

In this paper we show that there is measurable information in the articulatory system which
can help to disambiguate the acoustic signal. We measure directly the movement of the lips …

This paper describes the acoustic-to-articulatory inversion mapping using a Gaussian
Mixture Model (GMM). Correspondence of an acoustic parameter and an articulatory …

Prior research has shown that articulatory information, if extracted properly from the speech
signal, can improve the performance of automatic speech recognition systems. However …

We propose that using a continuous trajectory model to describe an articulatory-based
feature set will address some of the shortcomings inherent in the hidden Markov model …

Recent techniques employ end-to-end systems to learn relevant features for several speech
related applications, including speech recognition, and speaker verification. In this work, we …