Frederik Stouten

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Nowadays read speech recognition already works pretty well, but the recognition of spontaneous speech is much more problematic. There are plenty of reasons for this, and we hypothesize that one of them is the regular occurrence of disfl-uencies in spontaneous speech. Disfluencies disrupt the normal course of the sentence and when for instance word(More)
It is often argued that acoustic-phonetic or articulatory features could be beneficial to automatic speech recognition because they provide a convenient interface between the acoustic and the linguistic level. Former research has shown that a combination of acoustic and articulatory information can lead to improved ASR. However there exists no purely(More)
Nowadays, automatic speech recognizers have become quite good in recognizing well prepared fluent speech (e.g. news readings). However, the recognition of spontaneous speech is still problematic. Some important reasons for this are that spontaneous speech is usually less articulated and contains a lot of disfluencies. In this paper, a new methodology for(More)
It is a challenge to develop a speech recognizer that can handle the kind of lexicons encountered in an automatic attendant or car navigation application. Such lexicons can contain several 100K entries, mainly proper names. Many of these names are of a foreign origin, and native speakers can pronounce them in different ways, ranging from a completely(More)
The development of an automatic speech recognizer (ASR) that can accurately recognize spoken names belonging to a large lexicon, is still a big challenge. One of the bottlenecks is that many names contain elements of a foreign language origin, and native speakers can adopt very different pronunciations of these elements, ranging from completely nativized to(More)
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