Publications

Abstract

Despite advances in automatic speech recognition (ASR), human input is still essential to produce research-grade segmentations of speech data. Con- ventional approaches to manual segmentation are very labour-intensive. We introduce POnSS, a browser-based system that is specialized for the task of segmenting the onsets and offsets of words, that combines aspects of ASR with limited human input. In developing POnSS, we identified several sub- tasks of segmentation, and implemented each of these as separate interfaces for the annotators to interact with, to streamline their task as much as possible. We evaluated segmentations made with POnSS against a base- line of segmentations of the same data made conventionally in Praat. We observed that POnSS achieved comparable reliability to segmentation us- ing Praat, but required 23% less annotator time investment. Because of its greater efficiency without sacrificing reliability, POnSS represents a distinct methodological advance for the segmentation of speech data.

Abstract

Many psycholinguistic models of speech sequence planning make claims about the onset and offset times of planning units, such as words, syllables, and phonemes. These predictions typically go untested, however, since psycholinguists have assumed that the temporal dynamics of the speech signal is a poor index of the temporal dynamics of the underlying speech planning process. This article argues that this problem is tractable, and presents and validates two simple metrics that derive planning unit onset and offset times from the acoustic signal and articulatographic data.

Abstract

The question of whether intonation events have a categorical mental representation has long been a puzzle in prosodic research, and one that experiments testing production and perception across category boundaries have failed to definitively resolve. This paper takes the alternative approach of looking for evidence of structure within a postulated category by testing for a Perceptual Magnet Effect (PME). PME has been found in boundary tones but has not previously been conclusively found in pitch accents. In this investigation, perceived goodness and discriminability of re-synthesised Dutch nuclear rise contours (L*H H%) were evaluated by naive native speakers of Dutch. The variation between these stimuli was quantified using a polynomial-parametric modelling approach (i.e. the SOCoPaSul model) in place of the traditional approach whereby excursion size, peak alignment and pitch register are used independently of each other to quantify variation between pitch accents. Using this approach to calculate the acoustic-perceptual distance between different stimuli, PME was detected: (1) rated goodness, decreased as acoustic-perceptual distance relative to the prototype increased, and (2) equally spaced items far from the prototype were less frequently generalised than equally spaced items in the neighbourhood of the prototype. These results support the concept of categorically distinct intonation events.