Changes in magnitude and variability of duration, fundamental frequency, formant frequencies, and spectral envelope of children's speech are investigated as a function of age and gender using data obtained from 436 children, ages 5 to 17 years, and 56 adults. The results confirm that the reduction in magnitude and within-subject variability of both temporal and spectral acoustic parameters with age is a major trend associated with speech development in normal children. Between ages 9 and 12, both magnitude and variability of segmental durations decrease significantly and rapidly, converging to adult levels around age 12. Within-subject fundamental frequency and formant-frequency variability, however, may reach adult range about 2 or 3 years later. Differentiation of male and female fundamental frequency and formant frequency patterns begins at around age 11, becoming fully established around age 15. During that time period, changes in vowel formant frequencies of male speakers is approximately linear with age, while such a linear trend is less obvious for female speakers. These results support the hypothesis of uniform axial growth of the vocal tract for male speakers. The study also shows evidence for an apparent overshoot in acoustic parameter values, somewhere between ages 13 and 15, before converging to the canonical levels for adults. For instance, teenagers around age 14 differ from adults in that, on average, they show shorter segmental durations and exhibit less within-subject variability in durations, fundamental frequency, and spectral envelope measures.

Abstract-Multimodal streams of sensory information are naturally parsed and integrated by humans using signal-level feature extraction and higher-level cognitive processes. Detection of attention-invoking audiovisual segments is formulated in this work on the basis of saliency models for the audio, visual and textual information conveyed in a video stream. Aural or auditory saliency is assessed by cues that quantify multifrequency waveform modulations, extracted through nonlinear operators and energy tracking. Visual saliency is measured through a spatiotemporal attention model driven by intensity, color and orientation. Textual or linguistic saliency is extracted from partof-speech tagging on the subtitles information available with most movie distributions. The individual saliency streams, obtained from modality-depended cues, are integrated in a multimodal saliency curve, modeling the time-varying perceptual importance of the composite video stream and signifying prevailing sensory events. The multimodal saliency representation forms the basis of a generic, bottom-up video summarization algorithm. Different fusion schemes are evaluated on a movie database of multimodal saliency annotations with comparative results provided across modalities. The produced summaries, based on low-level features and content-independent fusion and selection, are of subjectively high aesthetic and informative quality.

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The dynamics of airflow during speech production may often result in some small or large degree of turbulence. In this paper, the geometry of speech turbulence as reflected in the fragmentation of the time signal is quantified by using fractal models. An efficient algorithm for estimating the short-time fractal dimension of speech signals based on multiscale morphological filtering is described, and its potential for speech segmentation and phonetic classification discussed. Also reported are experimental results on using the short-time fractal dimension of speech signals at multiple scales as additional features in an automatic speech-recognition system using hidden Markov models, which provide a modest improvement in speech-recognition performance.

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