Timo Mertens

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We present a lattice-based STD method for German broadcast news data and compare it to a previously proposed fuzzy search. Due to the important out-of-vocabulary (OOV) problem in German, we evaluate suitable subword indexing units for lattice retrieval. Hybrid lattice retrieval of words and subwords is investigated because of the robust nature of words as(More)
We describe how complementary search spaces, addressed by two different methods used in Spoken Term Detection (STD), can be merged for German subword STD. We propose fuzzy-search techniques on lattices to narrow the gap between sub-word and word retrieval. The first technique is based on an edit-distance, where no a priori knowledge about confusions is(More)
Phonetic features have been proposed to overcome performance degradation in spectral speaker recognition in difficult acoustic conditions. The harmful effect of those conditions, however, is not restricted to spectral systems but also affects the performance of the open-loop phone recognisers on which pho-netic systems are based. In automatic speech(More)
—We present a framework for learning a pronunciation lexicon for an Automatic Speech Recognition (ASR) system from multiple utterances of the same training words, where the lexical identities of the words are unknown. Instead of only trying to learn pronunciations for known words we go one step further and try to learn both spelling and pronunciation in a(More)
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