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The focus in automatic speech recognition (ASR) research has gradually shifted from isolated words to conversational speech. Consequently, the amount of pronunciation variation present in the speech under study has gradually increased. Pronunciation variation will deteriorate the performance of an ASR system if it is not well accounted for. This is probably(More)
In this paper, we examine the relationship between pedagogy and technology in Computer Assisted Pronunciation Training (CAPT) courseware. First, we will analyse available literature on second language pronunciation teaching and learning in order to derive some general guidelines for effective training. Second, we will present an appraisal of various CAPT(More)
This paper describes two experiments aimed at exploring the relationship between objective properties of speech and perceived fluency in read and spontaneous speech. The aim is to determine whether such quantitative measures can be used to develop objective fluency tests. Fragments of read speech (Experiment 1) of 60 non-native speakers of Dutch and 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)
To determine whether expert fluency ratings of read speech can be predicted on the basis of automatically calculated temporal measures of speech quality, an experiment was conducted with read speech of 20 native and 60 non-native speakers of Dutch. The speech material was scored for fluency by nine experts and was then analyzed by means of an automatic(More)
The current emphasis in second language teaching lies in the achievement of communicative effectiveness. In line with this approach, pronunciation training is nowadays geared towards helping learners avoid serious pronunciation errors, rather than eradicating the finest traces of foreign accent. However, to devise optimal pronunciation training programmes,(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)
There are various kinds o f adaptation which can be used to enhance the perform ance o f automatic speech recognizers. This paper is about pronunciation adaptation at the lexical level, i.e. about m odeling pronunciation variation at the lexical level. In the early years o f automatic speech recognition (ASR) research, the amount o f pronunciation variation(More)
Although the success of automatic speech recognition (ASR)-based Computer Assisted Pronunciation Training (CAPT) systems is increasing, little is known about the pedagogical effectiveness of these systems. This is particularly regrettable because ASR technology still suffers from limitations that may result in the provision of erroneous feedback, possibly(More)
We studied the frequencies of phone and syllable deletions in spontaneous Dutch, and the extent to which such deletions are influenced by the various linguistic and sociolinguistic factors represented in the transcriptions, word segmentations and metadata of the Spoken Dutch Corpus. In addition to providing insight into the frequencies of phone and syllable(More)