Phoneme recognition using time-delay neural networks

@article{Waibel1989PhonemeRU,
  title={Phoneme recognition using time-delay neural networks},
  author={Alexander H. Waibel and Toshiyuki Hanazawa and Geoffrey E. Hinton and Kiyohiro Shikano and Kevin J. Lang},
  journal={IEEE Trans. Acoust. Speech Signal Process.},
  year={1989},
  volume={37},
  pages={328-339}
}
The authors present a time-delay neural network (TDNN) approach to phoneme recognition which is characterized by two important properties: (1) using a three-layer arrangement of simple computing units, a hierarchy can be constructed that allows for the formation of arbitrary nonlinear decision surfaces, which the TDNN learns automatically using error backpropagation; and (2) the time-delay arrangement enables the network to discover acoustic-phonetic features and the temporal relationships between them independently of position in time and therefore not blurred by temporal shifts in the input. [] Key Method

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It is shown that the TDNN "invented" well-known acoustic-phonetic features and the temporal relationships between them are indeendent of position in time and hence not blurred by temporal shifts in the input.

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  • 1992
TLDR
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  • 1991
TLDR
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  • Computer Science
    1990 IJCNN International Joint Conference on Neural Networks
  • 1990
TLDR
A structure of neural networks based on the integration of time-delay neural networks which have several TDNNs separated according to the duration of phonemes is described for speaker-independent and context-independent phoneme recognition.

Continuous Speech Phoneme Recognition Using Dynamic Artificial Neural Networks

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The main objective of this paper is the investigation of dynamic ANN's, namely the Time-Delay Neural Networks (TDNN) and Recurrent Neural networks (RNN) - that are the most suitable for recognition of time se- quences.

Tunable time delay neural networks for isolated word recognition

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    Proceedings IEEE Southeastcon '95. Visualize the Future
  • 1995
TLDR
The proposed system is a modification of the original time delay neural network structure of Waibel et al. (1989) and consists of a group of sub-nets, and each isolated word or phoneme to be recognized corresponds to one sub-net.
...

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