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With the distribution of speech technology products all over the world, the portability to new target languages becomes a practical concern. As a consequence our research focuses on the question of how to port LVCSR systems in a fast and efficient way. More specifically we want to estimate acoustic models for a new target language using speech data from(More)
The performance of speech recognition systems is consistently poor on non-native speech. The challenge for non-native speech recognition is to maximize the recognition performance with small amount of non-native data available. In this paper we report on the acoustic modeling adaptation for the recognition of non-native speech. Using non-native data from(More)
With the distribution of speech technology products all over the world, the fast and efficient portability to new target languages becomes a practical concern. In this paper we explore the relative effectiveness of adapting multilingual LVCSR systems to a new target language with limited adaptation data. For this purpose we introduce a polyphone decision(More)
With the distribution of speech products all over the world, the portability to new target languages becomes a practical concern. As a consequence our research focuses on rapid transfer of LVCSR systems to other languages. In former studies we evaluated the performance if limited adaptation data is available. Particularly for very time constrained tasks and(More)
We integrated the Latent Dirichlet Allocation (LDA) approach, a latent semantic analysis model, into unsupervised language model adaptation framework. We adapted a background language model by minimizing the Kullback-Leibler divergence between the adapted model and the background model subject to a constraint that the marginalized unigram probability(More)
When developing synthesizers for new languages one must select a phoneset, record phonetically balanced sentences, build up a pronunciation lexicon, and evaluate the results. An objective measure of voice quality can be very useful, provided it is calibrated across multiple speakers, languages, and databases. As a substitute for full listening tests, this(More)