Burst segmentation and evaluation of acoustic cues

This paper investigates burst segmentation for the evaluation of acoustic cues used to identify unvoiced French stops. Unlike other works which utilize a fixed length window, our approach consists in segmenting bursts into transient and frication noise. The transient is found by minimizing the sum of spectral variances of transient and frication noise over the burst. The spectral variance criterion has the advantage of being sensitive both to energy deviations and spectral variations. Additional correction procedures augment the robustness of the segmentation against the presence of spurious noises during the closure and the determination of the voicing onset with delay. The relevance of our segmentation method has been evaluated by comparing the characteristics of the main spectral peak (energy prominence versus frequency) in the transient segmented by our method with those of the full burst. Our experiments showed that bursts segmented by our method allow a better discrimination between the three places of articulation.