Results 41 to 50 of about 76,886 (181)
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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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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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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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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Towards end-to-end speech recognition with transfer learning
EURASIP Journal on Audio, Speech, and Music Processing, 2018 A transfer learning-based end-to-end speech recognition approach is presented in two levels in our framework. Firstly, a feature extraction approach combining multilingual deep neural network (DNN) training with matrix factorization algorithm is ...
Chu-Xiong Qin, Dan Qu, Lian-Hai Zhang
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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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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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Simultaneous Neural Machine Translation using Connectionist Temporal Classification
CoRR, 2019 Simultaneous machine translation is a variant of machine translation that starts the translation process before the end of an input. This task faces a trade-off between translation accuracy and latency. We have to determine when we start the translation for observed inputs so far, to achieve good practical performance. In this work, we propose a neural
Katsuki Chousa +2 more
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Sound Event Detection with Sequentially Labelled Data Based on Connectionist Temporal Classification and Unsupervised Clustering [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019 Sound event detection (SED) methods typically rely on either strongly labelled data or weakly labelled data. As an alternative, sequentially labelled data (SLD) was proposed.
Yuanbo Hou +3 more
semanticscholar +1 more source
˜The œinternational Arab journal of information technology, 2020 Automatic classification of dynamic hand gesture is challenging due to the large diversity in a different class of gesture, Low resolution, and it is performed by finger. Due to a number of challenges many researchers focus on this area.
S. Patel, R. Makwana
semanticscholar +1 more source