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Exploring discrete wavelet transforms for bimodal speech recognition [PDF]
Serbian Journal of Electrical EngineeringDiscrete Wavelet Transforms (DWTs) provide time–frequency representations that are well suited for nonstationary signals such as speech. This study presents a comparison of four wavelet families (Daubechies, Symlets, Coiflets, and Biorthogonal) for ...
Marković Branko +2 more
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Frontiers in Computational Neuroscience, 2022 IntroductionIn recent years, machines powered by deep learning have achieved near-human levels of performance in speech recognition. The fields of artificial intelligence and cognitive neuroscience have finally reached a similar level of performance ...
Cai Wingfield +9 more
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Sadhana, 1986 Speech recognition, which remained on the fringes of commercial interest for many years, came into prominence recently due to the support extended to this research area by the Advanced Research Projects Agency of theusa. More recently, this area of research has received added impetus due to the priority assigned to the development of fifth generation ...
P V S Rao, K K Paliwal
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Audio-Visual Speech and Gesture Recognition by Sensors of Mobile Devices
Sensors, 2023 Audio-visual speech recognition (AVSR) is one of the most promising solutions for reliable speech recognition, particularly when audio is corrupted by noise. Additional visual information can be used for both automatic lip-reading and gesture recognition.
Dmitry Ryumin +2 more
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Automatic Speech Recognition from Neural Signals: A Focused Review
Frontiers in Neuroscience, 2016 Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might
Christian Herff, Tanja Schultz
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Automatic testing of speech recognition [PDF]
International Journal of Audiology, 2009 Speech reception tests are commonly administered by manually scoring the oral response of the subject. This requires a test supervisor to be continuously present. To avoid this, a subject can type the response, after which it can be scored automatically.
Francart, Tom +2 more
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Speech production knowledge in automatic speech recognition [PDF]
The Journal of the Acoustical Society of America, 2007 Although much is known about how speech is produced, and research into speech production has resulted in measured articulatory data, feature systems of different kinds, and numerous models, speech production knowledge is almost totally ignored in current mainstream approaches to automatic speech recognition.
King, Simon +5 more
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A Method Improves Speech Recognition with Contrastive Learning in Low-Resource Languages
Applied Sciences, 2023 Building an effective automatic speech recognition system typically requires a large amount of high-quality labeled data; However, this can be challenging for low-resource languages.
Lixu Sun, Nurmemet Yolwas, Lina Jiang
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Likelihood-Maximizing-Based Multiband Spectral Subtraction for Robust Speech Recognition
EURASIP Journal on Advances in Signal Processing, 2009 Automatic speech recognition performance degrades significantly when speech is affected by environmental noise. Nowadays, the major challenge is to achieve good robustness in adverse noisy conditions so that automatic speech recognizers can be used in ...
Bagher BabaAli +2 more
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KsponSpeech: Korean Spontaneous Speech Corpus for Automatic Speech Recognition
Applied Sciences, 2020 This paper introduces a large-scale spontaneous speech corpus of Korean, named KsponSpeech. This corpus contains 969 h of general open-domain dialog utterances, spoken by about 2000 native Korean speakers in a clean environment. All data were constructed
Jeong-Uk Bang +9 more
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