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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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Mikel Penagarikano, Amparo Varona, Germán Bordel and Luis Javier Rodriguez-Fuentes
In this paper, a semisupervised speech data extraction method is presented and applied to create a new dataset designed for the development of fully bilingual Automatic Speech Recognition (ASR) systems for Basque and Spanish. The dataset is drawn from an...
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Younggil Kim
Power control in an RS-coded orthogonal frequency division multiplex (OFDM) system with error-and-erasure correction decoding in Rayleigh fading channels was investigated. The power of each symbol within a codeword was controlled to reduce the codeword e...
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Juan Zuluaga-Gomez, Iuliia Nigmatulina, Amrutha Prasad, Petr Motlicek, Driss Khalil, Srikanth Madikeri, Allan Tart, Igor Szoke, Vincent Lenders, Mickael Rigault and Khalid Choukri
Voice communication between air traffic controllers (ATCos) and pilots is critical for ensuring safe and efficient air traffic control (ATC). The handling of these voice communications requires high levels of awareness from ATCos and can be tedious and e...
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Juan Carlos Atenco, Juan Carlos Moreno and Juan Manuel Ramirez
In this work we present a bimodal multitask network for audiovisual biometric recognition. The proposed network performs the fusion of features extracted from face and speech data through a weighted sum to jointly optimize the contribution of each modali...
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Eduardo Medeiros, Leonel Corado, Luís Rato, Paulo Quaresma and Pedro Salgueiro
Automatic speech recognition (ASR), commonly known as speech-to-text, is the process of transcribing audio recordings into text, i.e., transforming speech into the respective sequence of words. This paper presents a deep learning ASR system optimization ...
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Juan Zuluaga-Gomez, Amrutha Prasad, Iuliia Nigmatulina, Petr Motlicek and Matthias Kleinert
In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoke...
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Mariana Martínez-Castrejón, Enrique J. Flores-Munguía, Oscar Talavera-Mendoza, América L. Rodríguez-Herrera, Omar Solorza-Feria, Osbelia Alcaraz-Morales, Jazmin A. López-Díaz and Giovanni Hernández-Flores
Climate change, urbanization, and population growth, particularly in urban areas such as Acapulco, Mexico, put pressure on water availability, where although surrounded by water, the inhabitants lack enough good-quality water, especially in the rainy sea...
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Juan M. Perero-Codosero, Fernando M. Espinoza-Cuadros and Luis A. Hernández-Gómez
This paper describes a comparison between hybrid and end-to-end Automatic Speech Recognition (ASR) systems, which were evaluated on the IberSpeech-RTVE 2020 Speech-to-Text Transcription Challenge. Deep Neural Networks (DNNs) are becoming the most promisi...
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Sakshi Dua, Sethuraman Sambath Kumar, Yasser Albagory, Rajakumar Ramalingam, Ankur Dumka, Rajesh Singh, Mamoon Rashid, Anita Gehlot, Sultan S. Alshamrani and Ahmed Saeed AlGhamdi
Deep learning-based machine learning models have shown significant results in speech recognition and numerous vision-related tasks. The performance of the present speech-to-text model relies upon the hyperparameters used in this research work. In this re...
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