This paper describes the acoustic-to-articulatory inversion mapping using a Gaussian Mixture Model (GMM). Correspondence of an acoustic parameter and an articulatory parameter is modeled by the GMM trained using the parallel acousticarticulatory data. We measure the performance of the GMMbased mapping and investigate the effectiveness of using multiple acoustic frames as an input feature and us...

This paper presents the data on the anticipatory coarticulation of C2 and V2 on V1 in V1#C2V2 sequences in Standard Chinese. Electropalatographic measures and F2 trajectory were obtained to define the articulatory and F2 targets for V1 as well as the displacement for articulatory and F2 transition of V1. Results show that the articulatory target is affected only by C2 place, while C2 place, C2 ...

We present here the “labiophone”, a virtual system for audio-visual speech communication. A clone of the speaker is animated at distance by articulatory movements extracted from the speaker’s image and captured thanks to a video-camera centered on the speaker’s face. The clone consists of a mesh driven by a few articulatory parameters and clothed by blended textures. The characteristics of the ...

Kinematic articulatory data are important for researches of speech production, articulatory speech synthesis, robust speech recognition, and speech inversion. Electromagnetic Articulograph (EMA) is a widely used instrument for collecting kinematic articulatory data. However, in EMA experiment, one or more coils attached to articulators are possible to be mistracked due to various reasons. To ma...

This paper describes a segmental feature extraction and speech coding method in an acousticarticulatory domain using nomograms that represent a mapping between formant frequencies and articulatory parameters. The vocal tract model is a modified Fant model, in which we newly introduced a parameter for successively adjusting vocal tract lengths. We investigated first the relationship between form...

This paper presents an investigation into predicting the movement of a speaker’s mouth from text input using hidden Markov models (HMM). A corpus of human articulatory movements, recorded by electromagnetic articulography (EMA), is used to train HMMs. To predict articulatory movements for input text, a suitable model sequence is selected and a maximum-likelihood parameter generation (MLPG) algo...

Our approach to audiovisual articulatory synthesis involves the development of Virtual Talking Heads that integrate the articulatory, aerodynamic and acoustic phenomena underlying speech production. Specifically, these Talking Heads are faithful clones of the speakers whose data the various models are based on. Our contribution presents some of the results achieved at ICP in this domain: 3D oro...

This paper describes a segmental feature extraction and speech coding method in an acousticarticulatory domain using nomograms that represent a mapping between formant frequencies and articulatory parameters. The vocal tract model is a modified Fant model, in which we newly introduced a parameter for successively adjusting vocal tract lengths. We investigated first the relationship between form...

Articulatory information can support learning or remediating pronunciation of a second language (L2). This paper describes an electromagnetic articulometer-based visual-feedback approach using an articulatory target presented in real-time to facilitate L2 pronunciation learning. This approach trains learners to adjust articulatory positions to match targets for a L2 vowel estimated from product...