Using multi-layer neural networks to estimate the probabilities of word sequences is a promising research area in statistical language modeling, with applications in speech recogn...
Hai Son Le, Alexandre Allauzen, Guillaume Wisniews...
Maximum-Likelihod Linear Regression (MLLR) transform coefficients have shown to be useful features for text-independent speaker recognition systems. These use MLLR coefficients ...
This paper presents a discriminative training (DT) approach to irrelevant variability normalization (IVN) based training of feature transforms and hidden Markov models for large v...
Abstract. In automatic sign language translation, one of the main problems is the usage of spatial information in sign language and its proper representation and translation, e.g. ...
Long-span language models that capture syntax and semantics are seldom used in the first pass of large vocabulary continuous speech recognition systems due to the prohibitive sea...
Anoop Deoras, Tomas Mikolov, Stefan Kombrink, Mart...