The aim of this study is to apply a state-of-the-art speech emotion recognition engine on the detection of microsleep endangered sleepiness states. Current approaches in speech em...
High noise robustness has been achieved in speech recognition by using sparse exemplar-based methods with spectrogram windows spanning up to 300 ms. A downside is that a large exe...
Antti Hurmalainen, Jort F. Gemmeke, Tuomas Virtane...
Abstract. Long Short-Term Memory (LSTM) recurrent neural networks (RNNs) are local in space and time and closely related to a biological model of memory in the prefrontal cortex. N...
Current alternatives for language modeling are statistical techniques based on large amounts of training data, and hand-crafted context-free or finite-state grammars that are diff...
John Dowding, Beth Ann Hockey, Jean Mark Gawron, C...
This paper investigates the automatic recognition of emotion from spoken words by vector space modeling vs. string kernels which have not been investigated in this respect, yet. A...