Inner Lips Parameter Estimation based on Adaptive Ellipse Model

Li Liu (1) , Gang Feng (2) , Denis Beautemps (1)

1 GIPSA-CRISSP - GIPSA - Cognitive Robotics, Interactive Systems, & Speech Processing
2 GIPSA-VSLD - GIPSA - Voix Systèmes Linguistiques et Dialectologie

In this paper, a novel automatic method using an adaptive ellipse model to estimate inner lips parameters (inner lips width A and height B) of speakers without any artifices is presented. Color based image processing is first applied to delimit preliminary inner lips. A single discontinuity elimination combining horizontal and vertical filling are used to obtain a binary inner lips image as complete as possible. After the pre-processing steps, an optimal adaptive ellipse is determined to match the inner lips, giving A and B parameters. The proposed method is evaluated on 4693 images of three French speakers including one Cued Speech (CS) speaker. It obtains RMSE of 3.37 mm for A parameter and of 0.84 mm for B parameter which outperform the baseline of inner lips parameter estimation in the state of the art. Moreover, CS recognition based on 34 French phonemes shows that using the estimated two parameters achieves an accuracy which is comparable to that using raw lips ROI.

Keywords: inner lips contour parameter; image processing; Index Terms: Adaptive Ellipse Model; Cued Speech

Domains: Engineering Sciences [physics]; Signal and Image processing

Li Liu, Gang Feng, Denis Beautemps. Inner Lips Parameter Estimation based on Adaptive Ellipse Model. AVSP 2017 - 14th International Conference on Auditory-Visual Speech Processing, Aug 2017, Stockholm, Sweden. ⟨hal-01848508⟩