Judith. M. Kessens

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In this article, we address the issue of using a continuous speech recognition tool to obtain phonetic or phonological representations of speech. Two experiments were carried out in which the performance of a continuous speech recognizer (CSR) was compared to the performance of expert listeners in a task of judging whether a number of prespecified phones(More)
In this paper, the performance of an automatic transcription tool corpus is by modeling pronunciation variation [2]. is evaluated. The transcription tool is a continuous speech Another way of obtaining models which are less recognizer (CSR) which can be used to select pronunciation contaminated is to train PMs on read speech. It is well known variants (i.e.(More)
In this paper we use a data-driven (DD) rule-based method for modeling pronunciation variation. Error analysis is performed in order to gain insight into the effect of pronunciation variation modeling. This analysis shows that although modeling pronunciation variation brings about improvements, deteriorations are also introduced. A strong correlation is(More)
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