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Lizhen Jia, Yanyan Xu and Dengfeng Ke
Recent speech enhancement studies have mostly focused on completely separating noise from human voices. Due to the lack of specific structures for harmonic fitting in previous studies and the limitations of the traditional convolutional receptive field, ...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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Dan Ungureanu, Stefan-Adrian Toma, Ion-Dorinel Filip, Bogdan-Costel Mocanu, Iulian Aciobani?ei, Bogdan Marghescu, Titus Balan, Mihai Dascalu, Ion Bica and Florin Pop
The evolution of Natural Language Processing technologies transformed them into viable choices for various accessibility features and for facilitating interactions between humans and computers. A subset of them consists of speech processing systems, such...
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Jeong-Sik Park and Na Geng
Most conventional speech recognition systems have mainly concentrated on voice-driven control of personal user devices such as smartphones. Therefore, a speech recognition system used in a special environment needs to be developed in consideration of the...
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