# Neural Networks for Keyword Spotting on IoT Devices

arXiv: https://arxiv.org/abs/2101.00693 · HTML: https://mlsanity.com/paper/2101.00693/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 11 references that are in the map.
- First posted on arXiv 3 Jan 2021.

## Builds on (most cited first, 2 of 2)

- [Convolutional Recurrent Neural Networks for Small-Footprint Keyword Spotting](https://mlsanity.com/paper/1703.05390/) (2017)
- [A Microphone Array and Voice Algorithm based Smart Hearing Aid](https://mlsanity.com/paper/1908.07324/) (2019)

## Abstract (arXiv)

We explore Neural Networks (NNs) for keyword spotting (KWS) on IoT devices like smart speakers and wearables. Since we target to execute our NN on a constrained memory and computation footprint, we propose a CNN design that. (i) uses a limited number of multiplies. (ii) uses a limited number of model parameters.