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@ -56,17 +56,17 @@ We plan to support a variaty of hardwares and platforms, including:
## 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),
[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
[paper](https://arxiv.org/pdf/1705.02411.pdf)
* A depthwise separable convolutional neural network for keyword spotting on an embedded system
[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(
[paper](https://arxiv.org/pdf/1705.02411.pdf))
* A depthwise separable convolutional neural network for keyword spotting on an embedded system(
[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)
* Hello Edge: Keyword Spotting on Microcontrollers
[paper](https://asmp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13636-020-00176-2.pdf))
* Hello Edge: Keyword Spotting on Microcontrollers(
[github](https://arxiv.org/pdf/1711.07128.pdf),
[paper](https://github.com/ARM-software/ML-KWS-for-MCU)
* An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
[paper](https://github.com/ARM-software/ML-KWS-for-MCU))
* An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling(
[github](http://github.com/locuslab/TCN),
[paper](https://arxiv.org/pdf/1803.01271.pdf)
[paper](https://arxiv.org/pdf/1803.01271.pdf))