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Binbin Zhang 2021-11-30 17:55:52 +08:00
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@ -56,17 +56,17 @@ We plan to support a variaty of hardwares and platforms, including:
## Reference ## Reference
* Mining Effective Negative Training Samples for Keyword Spotting( * Mining Effective Negative Training Samples for Keyword Spotting
[github]( https://github.com/jingyonghou/KWS_Max-pooling_RHE), ([github]( https://github.com/jingyonghou/KWS_Max-pooling_RHE),
[paper](https://www.microsoft.com/en-us/research/uploads/prod/2020/04/ICASSP2020_Max_pooling_KWS.pdf)) [paper](https://www.microsoft.com/en-us/research/uploads/prod/2020/04/ICASSP2020_Max_pooling_KWS.pdf))
* Max-pooling Loss Training of Long Short-term Memory Networks for Small-footprint Keyword Spotting( * Max-pooling Loss Training of Long Short-term Memory Networks for Small-footprint Keyword Spotting
[paper](https://arxiv.org/pdf/1705.02411.pdf)) ([paper](https://arxiv.org/pdf/1705.02411.pdf))
* A depthwise separable convolutional neural network for keyword spotting on an embedded system( * A depthwise separable convolutional neural network for keyword spotting on an embedded system
[github](https://github.com/PeterMS123/KWS-DS-CNN-for-embedded), ([github](https://github.com/PeterMS123/KWS-DS-CNN-for-embedded),
[paper](https://asmp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13636-020-00176-2.pdf)) [paper](https://asmp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13636-020-00176-2.pdf))
* Hello Edge: Keyword Spotting on Microcontrollers( * Hello Edge: Keyword Spotting on Microcontrollers
[github](https://arxiv.org/pdf/1711.07128.pdf), ([github](https://arxiv.org/pdf/1711.07128.pdf),
[paper](https://github.com/ARM-software/ML-KWS-for-MCU)) [paper](https://github.com/ARM-software/ML-KWS-for-MCU))
* An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling( * An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
[github](http://github.com/locuslab/TCN), ([github](http://github.com/locuslab/TCN),
[paper](https://arxiv.org/pdf/1803.01271.pdf)) [paper](https://arxiv.org/pdf/1803.01271.pdf))