Results 51 to 60 of about 1,183,917 (259)
Deep Speech Based End-to-End Automated Speech Recognition (ASR) for Indian-English Accents [PDF]
Automated Speech Recognition (ASR) is an interdisciplinary application of computer science and linguistics that enable us to derive the transcription from the uttered speech waveform. It finds several applications in Military like High-performance fighter aircraft, helicopters, air-traffic controller.
arxiv
The performance of automatic speech recognition systems degrades in the presence of emotional states and in adverse environments (e.g., noisy conditions).
Meysam Bashirpour+1 more
doaj +1 more source
Why has (reasonably accurate) Automatic Speech Recognition been so hard to achieve? [PDF]
Hidden Markov models (HMMs) have been successfully applied to automatic speech recognition for more than 35 years in spite of the fact that a key HMM assumption -- the statistical independence of frames -- is obviously violated by speech data.
Gillick, Larry, Wegmann, Steven
core
A Protection Scheme With Speech Processing Against Audio Adversarial Examples
Machine learning technologies have improved the accuracy of speech recognition systems, and devices using those systems, such as smart speakers and AI assistants, are now in wide use. However, speech recognition systems have security vulnerabilities.
Yuya Tarutani+3 more
doaj +1 more source
Speech Recognition for the iCub Platform [PDF]
This paper describes open source software (available at https://github.com/robotology/natural-speech) to build automatic speech recognition (ASR) systems and run them within the YARP platform. The toolkit is designed (i) to allow non-ASR experts to easily create their own ASR system and run it on iCub and (ii) to build deep learning-based models ...
Bertrand Higy+4 more
openaire +5 more sources
Speech Emotion Recognition Using an Enhanced Kernel Isomap for Human-Robot Interaction
Speech emotion recognition is currently an active research subject and has attracted extensive interest in the science community due to its vital application to human-robot interaction.
Shiqing Zhang+2 more
doaj +1 more source
Silent speech recognition breaks the limitations of automatic speech recognition when acoustic signals cannot be produced or captured clearly, but still has a long way to go before being ready for any real-life applications.
Jinghan Wu+15 more
doaj +1 more source
Two and three-dimensional visual articulatory models for pronunciation training and for treatment of speech disorders [PDF]
Visual articulatory models can be used for visualizing vocal tract articulatory speech movements. This information may be helpful in pronunciation training or in therapy of speech disorders.
Graf-Borttscheller, Verena+2 more
core
Assistive tools that recognize impaired speech due to neurological disorders are emerging and its a fairly complex task. An Intelligent Impaired Speech Recognition system helps persons with speech impairment to improve their interactions with outside ...
Vishnika Veni S, Chandrakala S
doaj +1 more source
Multilingual Speech Recognition
The speech-to-speech translation system Verbmobil requires a multilingual setting. This consists of recognition engines in the three languages German, English and Japanese that run in one common framework together with a language identification component which is able to switch between these recognizers.
Waibel, Alex+4 more
openaire +4 more sources