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Describes an audio dataset of spoken words designed to help train and evaluate keyword spotting systems.
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V. Panayotov, G. Chen, D. Povey, and S. Khudanpur, “Librispeech: an ASR corpus based on public domain audio books,” in Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2015
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T. N. Sainath and C. Parada, “Convolutional Neural Networks for Small-Footprint Keyword Spotting,” in Sixteenth Annual Conference of the International Speech Communication Association , 2015. [Online]. Available: https://www.isca-speech.org/archive/interspeech_2015/papers/i15_1478.pdf
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(2017) Speech commands dataset version 1. [Online]. Available: http://download.tensorflow.org/data/speech_commands_v0.01.tar.gz
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(2017) Mozilla common voice. [Online]. Available: https://voice.mozilla.org/en
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(2017) Hey siri: An on-device dnn-powered voice trigger for apple’s personal assistant. [Online]. Available: https://machinelearning.apple.com/2017/10/01/hey-siri.html
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(2017) Speech commands dataset test set version 1. [Online]. Available: http://download.tensorflow.org/data/speech_commands_test_set_v0.01.tar.gz
2017
Cited alongside, same era.
(2017) Tensorflow audio recognition tutorial. [Online]. Available: https://www.tensorflow.org/tutorials/audio_recognition
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B. McMahan and D. Rao, “Listening to the World Improves Speech Command Recognition,” ArXiv e-prints , Oct. 2017
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R. Tang and J. Lin, “Deep Residual Learning for Small-Footprint Keyword Spotting,” ArXiv e-prints , Oct. 2017
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J. Lee, T. Kim, J. Park, and J. Nam, “Raw Waveform-based Audio Classification Using Sample-level CNN Architectures,” ArXiv e-prints , Dec. 2017
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(2018) Implementation of set assignment algorithm. [Online]. Available: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/speech_commands/input_data.py#L61
2018
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(2018) Speech commands dataset test set version 2. [Online]. Available: http://download.tensorflow.org/data/speech_commands_test_set_v0.02.tar.gz
2018
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(2018) test_streaming_accuracy.cc source file. [Online]. Available: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/speech_commands/test_streaming_accuracy.cc
2018
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(2018) recognize_commands.cc source file. [Online]. Available: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/speech_commands/recognize_commands.cc
2018
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(2018) Speech commands dataset streaming test version 2. [Online]. Available: http://download.tensorflow.org/data/speech_commands_streaming_test_v0.02.tar.gz
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(2018) Speech commands dataset version 2. [Online]. Available: http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz
2018
Cited alongside, same era.
(2018) Linguistic data consortium. [Online]. Available: https://www.ldc.upenn.edu/
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(2018) Creative commons international attribution international 4.0 license. [Online]. Available: https://creativecommons.org/licenses/by/4.0/
2018
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(2018) The 5th chime speech separation and recognition challenge. [Online]. Available: http://spandh.dcs.shef.ac.uk/chime_challenge/data.html
2018
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(2018) Speech commands tutorial checkpoints. [Online]. Available: https://storage.googleapis.com/download.tensorflow.org/models/speech_commands_checkpoints.tar.gz
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L. Lai, N. Suda, and V. Chandra, “CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUs,” ArXiv e-prints , Jan. 2018
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S. Krishna Gouda, S. Kanetkar, D. Harrison, and M. K. Warmuth, “Speech Recognition: Keyword Spotting Through Image Recognition,” ArXiv e-prints , Mar. 2018
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