Results 11 to 20 of about 35,015 (307)
SVMs for Automatic Speech Recognition: A Survey [PDF]
, 2007 Hidden Markov Models (HMMs) are, undoubtedly, the most employed core technique for Automatic Speech Recognition (ASR). Nevertheless, we are still far from achieving high-performance ASR systems. Some alternative approaches, most of them based on Artificial Neural Networks (ANNs), were proposed during the late eighties and early nineties.
Rubén Solera-Ureña +5 more
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Automatic Speech Recognition Using Limited Vocabulary: A Survey
Applied Artificial Intelligence, 2022 Automatic Speech Recognition (ASR) is an active field of research due to its large number of applications and the proliferation of interfaces or computing devices that can support speech processing.
Jean Louis K. E Fendji +3 more
doaj +1 more source
Assessing the accuracy of automatic speech recognition for psychotherapy
npj Digital Medicine, 2020 Accurate transcription of audio recordings in psychotherapy would improve therapy effectiveness, clinician training, and safety monitoring. Although automatic speech recognition software is commercially available, its accuracy in mental health settings ...
Adam S. Miner +11 more
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Speech translation enhanced automatic speech recognition [PDF]
IEEE Workshop on Automatic Speech Recognition and Understanding, 2005., 2005 Nowadays official documents have to be made available in many languages, like for example in the EU with its 20 official languages. Therefore, the need for effective tools to aid the multitude of human translators in their work becomes easily apparent.
Paulik, Matthias +5 more
openaire +3 more sources
Automatic depression recognition by intelligent speech signal processing: A systematic survey
CAAI Transactions on Intelligence Technology, 2023 Depression has become one of the most common mental illnesses in the world. For better prediction and diagnosis, methods of automatic depression recognition based on speech signal are constantly proposed and updated, with a transition from the early ...
Pingping Wu +5 more
doaj +1 more source
Hybrid Models for Automatic Speech Recognition: a Comparison of Classical ANN and Kernel Based Methods [PDF]
, 2007 Support Vector Machines (SVMs) are state-of-the-art methods for machine learning but share with more classical Artificial Neural Networks (ANNs) the difficulty of their application to input patterns of non-fixed dimension.
Peláez-Moreno, Carmen +5 more
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Method for visual analysis of driver's face for automatic lip-reading in the wild
Компьютерная оптика, 2022 The paper proposes a method of visual analysis for automatic speech recognition of the vehicle driver. Speech recognition in acoustically noisy conditions is one of big challenges of artificial intelligence. The problem of effective automatic lip-reading
A.A. Axyonov +4 more
doaj +1 more source
EURASIP Journal on Audio, Speech, and Music Processing, 2010 In patients suffering from head and neck cancer, speech intelligibility is often restricted. For assessment and outcome measurements, automatic speech recognition systems have previously been shown to be appropriate for objective and quick evaluation of ...
Andreas Maier +7 more
doaj +1 more source
A Hybrid Speech Enhancement Algorithm for Voice Assistance Application
Sensors, 2021 In recent years, speech recognition technology has become a more common notion. Speech quality and intelligibility are critical for the convenience and accuracy of information transmission in speech recognition.
Jenifa Gnanamanickam +2 more
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Avoiding distortions due to speech coding and transmission errors [PDF]
, 1999 We have extended our previous research on a new approach to automatic speech recognition (ASR) in the GSM environment. Instead of recognizing from the decoded speech signal, our system works from the digital speech representation used by the GSM encoder.
Valverde Albacete, Francisco José +8 more
core +1 more source