Ulrich Bodenhausen

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In this work we describe a new method that adjusts time-delays and the widths of time-windows in artificial neural networks automatically. The input of the units are weighted by a gaussian input-window over time which allows the learning rules for the delays and widths to be derived in the same way as it is used for the weights. Our results on a phoneme(More)
In this paper we show how the Multi-State Time Delay Neural Network (MS-TDNN), which is already used successfully in continuous speech recognition tasks, can be applied both to on-line single character and cursive (continuous) handwriting recognition. The MS-TDNN integrates the high accuracy single character recognition capabilities of a TDNN with a(More)
| In this paper we report on our eeorts to combine speech and language processing toward multilingual spontaneous speech translation. The ongoing work extends our JANUS system eeort toward handling spontaneous spoken discourse and multiple languages. After an overview of the task, databases, and the system architecture we will focus on how connectionist(More)
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