Visual Feedback of Tongue Movement for Novel Speech Sound Learning

William F Katz, Sonya Mehta, William F Katz, Sonya Mehta

Abstract

Pronunciation training studies have yielded important information concerning the processing of audiovisual (AV) information. Second language (L2) learners show increased reliance on bottom-up, multimodal input for speech perception (compared to monolingual individuals). However, little is known about the role of viewing one's own speech articulation processes during speech training. The current study investigated whether real-time, visual feedback for tongue movement can improve a speaker's learning of non-native speech sounds. An interactive 3D tongue visualization system based on electromagnetic articulography (EMA) was used in a speech training experiment. Native speakers of American English produced a novel speech sound (/ɖ/; a voiced, coronal, palatal stop) before, during, and after trials in which they viewed their own speech movements using the 3D model. Talkers' productions were evaluated using kinematic (tongue-tip spatial positioning) and acoustic (burst spectra) measures. The results indicated a rapid gain in accuracy associated with visual feedback training. The findings are discussed with respect to neural models for multimodal speech processing.

Keywords: articulation therapy; audiovisual integration; electromagnetic articulography; second language learning; speech production; visual feedback.

Figures

Figure 1
Figure 1
Illustration of the Opti-Speech system, with subject wearing sensors and head-orientation glasses (lower right insert). A sample target sphere, placed in this example at the subject's alveolar ridge, is shown in red. A blue marker indicates the tongue tip/blade (TT) sensor.
Figure 2
Figure 2
Close-up of tongue avatar during a “hit” for the production of the voiced, retroflex, palatal stop consonant. The target sphere lights up green, providing visual feedback for the correct place of articulation.
Figure 3
Figure 3
Accuracy for five talkers producing a coronal palatal stop. Shaded regions indicate visual feedback conditions. Baseline (pre-training) and post-training phases are also indicated.
Figure 4
Figure 4
Overlapping plots of short-term spectra for bursts of voiced, coronal, palatal stops produced before and after EMA training. Correct place of articulation (hits) are marked in blue, and errors (misses) in red. Computed averages of incorrect pre-training (red) and correct post-training (blue) spectra are shown at right, for comparison.
Figure 5
Figure 5
Simplified version of ACT model (Kröger and Kannampuzha, 2008), showing input pathways for external audiovisual stimuli (oval at bottom right) and optional feedback circuits to the vocal tract (shaded box at bottom). Visual feedback (dotted line) is provided by either external (mirroring) or internal (instrumental augmented) routes.

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Source: PubMed

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