Future Speech Interfaces with Sensors and Machine Intelligence

Speech is the most spontaneous and natural means of communication, as well as the preferred modality for interacting with mobile or fixed electronic devices, but speech in-terfaces have drawbacks, such as a lack of user privacy; non-inclusivity for certain users; poor robustness in noisy conditions;...

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Other Authors: Denby, Bruce (Editor), Gábor Csapó, Tamás (Editor), Wand, Michael (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
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DOAB: description of the publication
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520 |a Speech is the most spontaneous and natural means of communication, as well as the preferred modality for interacting with mobile or fixed electronic devices, but speech in-terfaces have drawbacks, such as a lack of user privacy; non-inclusivity for certain users; poor robustness in noisy conditions; and the difficulty of creating complex man-machine interfaces. The Special Issue "Future Speech Interfaces with Sensors and Machine Intelligence" assembles eleven contributions that cover multimodal and silent speech interfaces; lip reading applications; novel sensors for speech interfaces; and enhanced speech inclusivity tools for future speech interfaces. The articles make important improvements beyond the state of the art, advancing the state of the art to new frontiers in some cases. Short summaries of all articles, grouped by topic, are presented, followed by a global commentary and evaluation. 
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653 |a modern standard Arabic 
653 |a subword units 
653 |a multi-head attention 
653 |a shared vocabulary 
653 |a self-attention 
653 |a 3D densely connected CNN 
653 |a 3D multi-layer feature fusion CNN 
653 |a convolutional neural network 
653 |a deep learning 
653 |a lipreading 
653 |a speech recognition 
653 |a visual speech recognition 
653 |a silent speech 
653 |a continuous-wave radar 
653 |a European Portuguese 
653 |a machine learning 
653 |a multimodal speech 
653 |a lip reading 
653 |a ultrasound tongue imaging 
653 |a pose estimation 
653 |a speech kinematics 
653 |a keypoints 
653 |a landmarks 
653 |a audio-visual speech recognition 
653 |a lip-reading 
653 |a application programming interface 
653 |a multi-modal interaction 
653 |a deep neural networks 
653 |a multi-view VSR 
653 |a attention mechanism 
653 |a spatial attention module 
653 |a local self-attention 
653 |a connectionist temporal classification 
653 |a text-to-lip 
653 |a speech synthesis 
653 |a text-to-speech 
653 |a speech-to-lip 
653 |a zero-shot adaptation 
653 |a generative models 
653 |a artificial intelligence 
653 |a objective measures 
653 |a hybrid models 
653 |a end-to-end recognition 
653 |a reliability measures 
653 |a decision fusion net 
653 |a articulation-to-speech synthesis 
653 |a silent speech interface 
653 |a speaker adaption 
653 |a voice conversion 
653 |a audiovisual speech recognition 
653 |a multimodal interaction 
653 |a edutainment 
653 |a virtual aquarium 
653 |a speech processing 
653 |a ultrasound imaging 
653 |a silent speech interfaces 
653 |a speech sensors 
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