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Phoneme recognition using time-delay neural networks

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Kevin J. LangAuthors Info & Claims

Readings in speech recognition

May 1990

Pages 393 - 404

Published: 01 May 1990 Publication History

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Wang HPan TAhsan M(2020)Hand-drawn electronic component recognition using deep learning algorithmInternational Journal of Computer Applications in Technology10.1504/ijcat.2020.10390562:1(13-19)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1504/ijcat.2020.103905
Wang YDeng YShen YJin HElkind EVeloso MAgmon NTaylor M(2019)A New Concept of Convex based Multiple Neural Networks StructureProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331836(1306-1314)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331836
Deng SZhang NZhang WChen JPan JChen H(2019)Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional NetworkCompanion Proceedings of The 2019 World Wide Web Conference10.1145/3308560.3317701(678-685)Online publication date: 13-May-2019
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Phoneme recognition using time-delay neural networks

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This paper describes a large-scale neural network architecture based on TDNN (Time-Delay Neural Network) for speaker-independent phoneme recognition which represents an advance over speaker-dependent and multispeaker phoneme recognition. Based on a ...
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This paper presents an evaluation of speaker-independent continuous phoneme recognition systems on the French speech database ESTER. The tested systems are syllable-based phoneme recognizers, i.e. they use syllables as basic units together with syllabic ...

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Readings in speech recognition

May 1990

629 pages

ISBN:1558601244

Editors:
Alex Waibel,
Kai-Fu Lee

Publisher

Morgan Kaufmann Publishers Inc.

San Francisco, CA, United States

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Published: 01 May 1990

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Wang HPan TAhsan M(2020)Hand-drawn electronic component recognition using deep learning algorithmInternational Journal of Computer Applications in Technology10.1504/ijcat.2020.10390562:1(13-19)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1504/ijcat.2020.103905
Wang YDeng YShen YJin HElkind EVeloso MAgmon NTaylor M(2019)A New Concept of Convex based Multiple Neural Networks StructureProceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems10.5555/3306127.3331836(1306-1314)Online publication date: 8-May-2019
https://dl.acm.org/doi/10.5555/3306127.3331836
Deng SZhang NZhang WChen JPan JChen H(2019)Knowledge-Driven Stock Trend Prediction and Explanation via Temporal Convolutional NetworkCompanion Proceedings of The 2019 World Wide Web Conference10.1145/3308560.3317701(678-685)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308560.3317701
Cheema NHosseini SSprenger JHerrmann EDu HFischer KSlusallek PMarchal MRohmer DThuerey NBeeler T(2018)Dilated temporal fully-convolutional network for semantic segmentation of motion capture dataProceedings of the Conference on Computer Animation10.2312/sca.20181185(5-6)Online publication date: 4-Jun-2018
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Zhao XWei YCai W(2018)Study on Infrared Stealth Performance Evaluation Based on Convolution Neural NetworkProceedings of the 3rd International Conference on Multimedia and Image Processing10.1145/3195588.3195603(62-67)Online publication date: 16-Mar-2018
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Khorasani FEsfeden HAbu-Ghazaleh NSarkar VOskin MInoue K(2018)In-register parameter caching for dynamic neural nets with virtual persistent processor specializationProceedings of the 51st Annual IEEE/ACM International Symposium on Microarchitecture10.1109/MICRO.2018.00038(377-389)Online publication date: 20-Oct-2018
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Krishna KLu LGimpel KLivescu K(2018)A Study of All-Convolutional Encoders for Connectionist Temporal Classification2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2018.8462210(5814-5818)Online publication date: 15-Apr-2018
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Speech recognition based on time-delay neural networks

Speaker-independent phoneme recognition using large-scale neural networks

Automatic syllable-based phoneme recognition using ESTER corpus

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