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

Previous research [9] suggests that Dutch learners of (British) English are not able to express sarcasm prosodically in their L2. The present study investigates whether explicit training on the prosodic markers of sarcasm in English can improve learners’ realisation of sarcasm. Sarcastic speech was elicited in short simulated telephone conversations between Dutch advanced learners of English and a native British English-speaking ‘friend’ in two sessions, fourteen days apart. Between the two sessions, participants were trained by means of (1) a presentation, (2) directed independent practice, and (3) evaluation of participants’ production and individual feedback in small groups. L1 British English-speaking raters subsequently evaluated the degree of sarcastic sounding in the participants’ responses on a five-point scale. It was found that significantly higher sarcasm ratings were given to L2 learners’ production obtained after the training than that obtained before the training; explicit training on prosody has a positive effect on learners’ production of sarcasm.

Abstract

Apraxia of Speech (AOS) is a motor speech disorder whose precise nature is still poorly understood. A recent behavioural experiment featuring a noise masking paradigm suggests that AOS reflects a disruption of feedforward control, whereas feedback control is spared and plays a more prominent role in achieving and maintaining segmental contrasts [10]. In the present study, we set out to validate the interpretation of AOS as a feedforward impairment by means of a series of computational simulations with the DIVA model [6, 7] mimicking the behavioural experiment. Simulation results showed a larger reduction in vowel spacing and a smaller vowel dispersion in the masking condition compared to the no-masking condition for the simulated feedforward deficit, whereas the other groups showed an opposite pattern. These results mimic the patterns observed in the human data, corroborating the notion that AOS can be conceptualized as a deficit in feedforward control