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Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...
Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...
Automatic speech recognition (ASR) systems incorporate expert knowledge of language or the linguistic expertise through the use of phone pronunciation lexicon (or dictionary) where each word is associated with a sequence of phones. The creation of phone pr ...
There is growing interest in using graphemes as subword units, especially in the context of the rapid development of hidden Markov model (HMM) based automatic speech recognition (ASR) system, as it eliminates the need to build a phoneme pronunciation lexic ...
Character-level Neural Machine Translation(NMT) models have recently achieved impressive results on many language pairs. They mainly do well for Indo-European language pairs, where the languages share the same writing system. However, for translating betwe ...
Sensors capable of detecting and classifying volatile organic compounds (VOC) have been gaining more attention by the advent of internet-of-things (IoT) enabled devices and integration of various sensing elements into hand-held and portable devices. The re ...
From the conceptualization to the evaluation of blended learning scenarios, teachers address multiple tasks, sometimes being overwhelmed on account of the required time and associated burden. To support teachers in this endeavor, we propose to connect the ...
Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on analy ...
State-of-the-art phoneme sequence recognition systems are based on hybrid hidden Markov model/artificial neural networks (HMM/ANN) framework. In this framework, the local classifier, ANN, is typically trained using Viterbi expectation-maximization algorith ...
The recognition during the second half of the 20th century of the essential role played by public spaces in the definition of qualitative urban life has led to a reconsideration of their design. This has occurred in many different forms, such as the emerge ...