Fabian Tomaschek

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Recent experiments showed that the perception of vowel length by German listeners exhibits the characteristics of categorical perception. The present study sought to find the neural activity reflecting categorical vowel length and the short-long boundary by examining the processing of non-contrastive durations and categorical length using MEG. Using(More)
The German vowel system shows a complex structure based on the interaction between vowel duration and formant structures between short and long cognates. This leads to the question how vowel duration is processed. The perception of vowel duration in German native speakers was tested by an identification test, a goodness rating and an adaptive discrimination(More)
A frequently replicated finding is that higher frequency words tend to be shorter and contain more strongly reduced vowels. However, little is known about potential differences in the articulatory gestures for high vs. low frequency words. The present study made use of electromagnetic articulography to investigate the production of two German vowels, [i](More)
It is commonly know that a word's frequency of use and its contextual predictability correlate with its spectral and temporal acoustic characteristics. Aylett and Turk (2004) proposed that the source of this variance is the speech production system's need to maintain a uniform information flow. In high information contexts the speech signal is expanded, in(More)
The German vowel system has a complex structure comprising a quantity distinction depending on lexical stress and syllable struc‐ ture. The present study investigated the neu‐ ral and behavioral processing of duration in vowels and non‐speech stimuli in German native speakers. The speech material consisted of a disyllabic, trochaic nonsense word /tat@/, in(More)
Sound units play a pivotal role in cognitive models of auditory comprehension. The general consensus is that during perception listeners break down speech into auditory words and subsequently phones. Indeed, cognitive speech recognition is typically taken to be computationally intractable without phones. Here we present a computational model trained on 20(More)
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