Prosodic Event Recognition using Convolutional Neural Networks with Context Information

This paper demonstrates the potential of convolutional neural networks (CNN) for detecting and classifying prosodic events on words, specifically pitch accents and phrase boundary tones, from frame-based acoustic features. Typical approaches use not only feature representations of the word in question but also its surrounding context. We show that adding position features indicating the current word benefits the CNN. In addition, this paper discusses the generalization from a speaker-dependent modelling approach to a speaker-independent setup. The proposed method is simple and efficient and yields strong results not only in speaker-dependent but also speaker-independent cases.Comment: Interspeech 2017 4 pages, 1 figur

Dimensions of Segmental Variability: Interaction of Prosody and Surprisal in Six Languages

Contextual predictability variation affects phonological and phonetic structure. Reduction and expansion of acoustic-phonetic features is also characteristic of prosodic variability. In this study, we assess the impact of surprisal and prosodic structure on phonetic encoding, both independently of each other and in interaction. We model segmental duration, vowel space size and spectral characteristics of vowels and consonants as a function of surprisal as well as of syllable prominence, phrase boundary, and speech rate. Correlates of phonetic encoding density are extracted from a subset of the BonnTempo corpus for six languages: American English, Czech, Finnish, French, German, and Polish. Surprisal is estimated from segmental n-gram language models trained on large text corpora. Our findings are generally compatible with a weak version of Aylett and Turk's Smooth Signal Redundancy hypothesis, suggesting that prosodic structure mediates between the requirements of efficient communication and the speech signal. However, this mediation is not perfect, as we found evidence for additional, direct effects of changes in surprisal on the phonetic structure of utterances. These effects appear to be stable across different speech rates