Results 31 to 40 of about 14,332 (195)
Mandarin recognition and improvement based on CTC criterion [PDF]
Jisuanji gongcheng, 2019 The cross-entropy criterion of mainstream neural network training classifies and optimizes each frame of acoustic data, while the continuous speech recognition uses the sequence-level transcription accuracy as the performance measurement.For this ...
ZHANG Limin,WANG Yanzhe,ZHANG Bingqiang,ZHU Nianbin
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Automatic Speech Recognition Method Based on Deep Learning Approaches for Uzbek Language
Sensors, 2022 Communication has been an important aspect of human life, civilization, and globalization for thousands of years. Biometric analysis, education, security, healthcare, and smart cities are only a few examples of speech recognition applications.
Abdinabi Mukhamadiyev +3 more
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Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition [PDF]
, 2018 Recently, the connectionist temporal classification (CTC) model coupled with recurrent (RNN) or convolutional neural networks (CNN), made it easier to train speech recognition systems in an end-to-end fashion.
Bengio, Yoshua +6 more
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IEEE Access, 2022 To solve the problem of the low recognition rate of continuous dynamic gestures in Chinese sign language, a non-invasive end-to-end continuous dynamic gesture recognition system combining Inertial Measurement Unit (IMU) signal and surface ...
Jinquan Li +3 more
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Probabilistic asr feature extraction applying context-sensitive connectionist temporal classification networks [PDF]
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 This paper proposes a novel automatic speech recognition (ASR) front-end that unites the principles of bidirectional Long Short-Term Memory (BLSTM), Connectionist Temporal Classification (CTC), and Bottleneck (BN) feature generation. BLSTM networks are known to produce better probabilistic ASR features than conventional multilayer perceptrons since ...
Wollmer, Martin +2 more
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IEEE Access, 2018 The end-to-end learning approaches were proposed for an arithmetic expression recognition task in the Baidu Meizu Deep Learning Competition by a deep convolutional neural network (DCNN) with parallel dense layers and component-connection-based detection ...
Yuxiang Jiang +2 more
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CNN-RNN BASED HANDWRITTEN TEXT RECOGNITION
ICTACT Journal on Soft Computing, 2021 At present most of the scripts are handwritten due to the ease of using a pen tip in place of a keyboard, hence errors are common due to illegibility of the human handwriting. To avoid this problem handwriting recognition is essential.
Hemanth G R +4 more
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Applied Sciences, 2021 State-of-the-art Optical Music Recognition (OMR) techniques follow an end-to-end or holistic approach, i.e., a sole stage for completely processing a single-staff section image and for retrieving the symbols that appear therein.
María Alfaro-Contreras +1 more
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, 2003 ACT is compared with a particular type of connectionist model that cannot handle symbols and use non-biological operations that cannot learn in real time. This focus continues an unfortunate trend of straw man "debates" in cognitive science.
Grossberg, Stephen
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Causalcall: Nanopore Basecalling Using a Temporal Convolutional Network
Frontiers in Genetics, 2020 Nanopore sequencing is promising because of its long read length and high speed. During sequencing, a strand of DNA/RNA passes through a biological nanopore, which causes the current in the pore to fluctuate. During basecalling, context-dependent current
Jingwen Zeng +5 more
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