We present a method that determines articulatory movements from speech acoustics using an HMM (Hidden Markov Model)-based speech production model. The model statistically generates speech acoustics and articulatory movements from a given phonemic string. It consists of HMMs of articulatory movements for each phoneme and an articulatory-to-acoustic mapping for each HMM state. For a given speech ...

This paper investigates the functional relationship between articulatory variability and stability of acoustic cues during American English /r/ production. The analysis of articulatory movement data on seven subjects shows that the extent of intra-subject articulatory variability along any given articulatory direction is strongly and inversely related to a measure of acoustic stability (the ext...

In this paper new EMMA data regarding European Portuguese nasals is presented. Some details about corpus constitution, recording and annotation is given. First results from analysis are presented. Quantitative analysis of velum movement was done for nasal vowels between stops. For the other contexts representative examples are presented and qualitatively analysed. In all contexts nasal vowels a...

This paper presents a new paradigm for code-switching event detection based on delta Bayesian Information Criterion (∆BIC). First, an automatic speech recognizer (ASR) and an articulatory feature (AF) detector are constructed. The intersyllable boundaries obtained from the ASR are regarded as the potential code-switching boundaries. To estimate the language likelihood, eigenvoice models (EVMs) ...

Acoustic-to-articulatory inverse mapping is a difficult problem because of its non-linear and oneto-many characteristics. We have previously developed a speech inversion method using a hidden Markov model (HMM)-based speech production model which takes into account the phonemespecific dynamic constraints of articulatory parameters. We found that the constraint significantly decreases the estima...

It is often argued that acoustic-phonetic or articulatory features could be beneficial to automatic speech recognition because they provide a convenient interface between the acoustic and the linguistic level. Former research has shown that a combination of acoustic and articulatory information can lead to improved ASR. However there exists no purely articulatory driven ASR system that outperfo...