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Found 2 papers, 1 papers with code
Cluster-based pruning techniques for audio data
In this work, we introduce, for the first time in the context of the audio domain, the k-means clustering as a method for efficient data pruning.
PEAF: Learnable Power Efficient Analog Acoustic Features for Audio Recognition
At the end of Moore's law, new computing paradigms are required to prolong the battery life of wearable and IoT smart audio devices.
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