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)
This paper describes how the performance of a continuous speech recognizer for Dutch has been improved by modeling within-word and crossword pronunciation variation. Within-word variants were automatically generated by applying five phonological rules to the words in the lexicon. For the within-word method, a significant improvement is found compared to the(More)
This paper describes a rule-based data-driven (DD) method to model pronunciation variation in automatic speech recognition (ASR). The DD method consists of the following steps. First, the possible pronunciation variants are generated by making each phone in the canonical transcription of the word optional. Next, forced recognition is performed in order to(More)
The first goal of this study was to investigate the effect of changing several properties of a continuous speech recognizer (CSR) on the automatic phonetic transcriptions generated by the same CSR. Our results show that the quality of the automatic transcriptions can be improved by using ÔshortÕ hidden Markov models (HMMs) and by reducing the amount of(More)
This article describes how the performance of a Dutch continuous speech recognizer was improved by modeling pronunciation variation. We propose a general procedure for modeling pronunciation variation. In short, it consists of adding pronunciation variants to the lexicon, retraining phone models and using language models to which the pronunciation variants(More)
This paper describes how the performance of a continuous speech recognizer for Dutch has been improved by modeling pronunciation variation. We used three methods in order to model pronunciation variation. First, within-word variation was dealt with. Phonological rules were applied to the words in the lexicon, thus automatically generating pronunciation(More)
This paper describes how the performance of a continuous speech recognizer for Dutch has been improved by modeling within-word and crossword pronunciation variation. A relative improvement of 8.8% in WER was found compared to baseline system performance. However, as WERs do not reveal the full effect of modeling pronunciation variation, we performed a(More)
In this paper a new measure of recognition accuracy is introduced which can be used when comparing the performance of two speech recognizers, to establish which is the better one. This metric combines the advantages of previous measures, but excludes their disadvantages. Essentially, the metric is an attempt to quantify the degree of recognition accuracy(More)
In this paper the performance of an automatic transcription tool is evaluated. The transcription tool is a Continuous Speech Recognizer (CSR) running in forced recognition mode. For evaluation the performance of the CSR was compared to that of nine expert listeners. Both man and the machine carried out exactly the same task: deciding whether a segment was(More)