# Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware

arXiv: https://arxiv.org/abs/1812.01739 · HTML: https://mlsanity.com/paper/1812.01739/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2018.

## Built on by (most cited first, 30 of 37)

- [A Spiking Neural Network for Image Segmentation](https://mlsanity.com/paper/2106.08921/) (2021)
- [Bottom-up and top-down approaches for the design of neuromorphic processing systems: Tradeoffs and synergies between natural and artificial intelligence](https://mlsanity.com/paper/2106.01288/) (2021)
- [Sub-mW Neuromorphic SNN audio processing applications with Rockpool and Xylo](https://mlsanity.com/paper/2208.12991/) (2022)
- [WaveSense: Efficient Temporal Convolutions with Spiking Neural Networks for Keyword Spotting](https://mlsanity.com/paper/2111.01456/) (2021)
- [Neuromorphic Computing is Turing-Complete](https://mlsanity.com/paper/2104.13983/) (2021)
- [DeepFire2: A Convolutional Spiking Neural Network Accelerator on FPGAs](https://mlsanity.com/paper/2305.05187/) (2023)
- [Detection of Fast-Moving Objects with Neuromorphic Hardware](https://mlsanity.com/paper/2403.10677/) (2024)
- [Stabilizing Spiking Neuron Training](https://mlsanity.com/paper/2202.00282/) (2022)
- [Collective control of modular soft robots via embodied Spiking Neural Cellular Automata](https://mlsanity.com/paper/2204.02099/) (2022)
- [Surrogate Gradient Spiking Neural Networks as Encoders for Large Vocabulary Continuous Speech Recognition](https://mlsanity.com/paper/2212.01187/) (2022)
- [Improvement of Spiking Neural Network with Bit Planes and Color Models](https://mlsanity.com/paper/2410.08229/) (2024)
- [Voltage-Dependent Synaptic Plasticity (VDSP): Unsupervised probabilistic Hebbian plasticity rule based on neurons membrane potential](https://mlsanity.com/paper/2203.11022/) (2022)
- [Evaluating Spiking Neural Network On Neuromorphic Platform For Human Activity Recognition](https://mlsanity.com/paper/2308.00787/) (2023)
- [Drone Detection Using a Low-Power Neuromorphic Virtual Tripwire](https://mlsanity.com/paper/2509.12997/) (2025)
- [Modern Neuromorphic AI: From Intra-Token to Inter-Token Processing](https://mlsanity.com/paper/2601.00245/) (2026)
- [N-DriverMotion: Driver motion learning and prediction using an event-based camera and directly trained spiking neural networks on Loihi 2](https://mlsanity.com/paper/2408.13379/) (2024)
- [Spiking Neural Networks for Low-Power Vibration-Based Predictive Maintenance](https://mlsanity.com/paper/2506.13416/) (2025)
- [Energy-Efficient Neuromorphic Computing for Edge AI: A Framework with Adaptive Spiking Neural Networks and Hardware-Aware Optimization](https://mlsanity.com/paper/2602.02439/) (2026)
- [Multi-Sample Online Learning for Spiking Neural Networks based on Generalized Expectation Maximization](https://mlsanity.com/paper/2102.03280/) (2021)
- [Desire Backpropagation: A Lightweight Training Algorithm for Multi-Layer Spiking Neural Networks based on Spike-Timing-Dependent Plasticity](https://mlsanity.com/paper/2211.05412/) (2022)
- [Exploring Tradeoffs in Spiking Neural Networks](https://mlsanity.com/paper/2212.09500/) (2022)
- [Stabilizing RNN Gradients through Pre-training](https://mlsanity.com/paper/2308.12075/) (2023)
- [Advanced Computing and Related Applications Leveraging Brain-inspired Spiking Neural Networks](https://mlsanity.com/paper/2309.04426/) (2023)
- [A versatile circuit for emulating active biological dendrites applied to sound localisation and neuron imitation](https://mlsanity.com/paper/2311.12861/) (2023)
- [Neuromorphic Spintronics](https://mlsanity.com/paper/2409.10290/) (2024)
- [Towards efficient keyword spotting using spike-based time difference encoders](https://mlsanity.com/paper/2503.15402/) (2025)
- [Frozen Backpropagation: Relaxing Weight Symmetry in Deep Spiking Neural Networks](https://mlsanity.com/paper/2505.13741/) (2025)
- [Energy-Efficient Deep Reinforcement Learning with Spiking Transformers](https://mlsanity.com/paper/2505.14533/) (2025)
- [Adaptive Spiking with Plasticity for Energy Aware Neuromorphic Systems](https://mlsanity.com/paper/2508.11689/) (2025)
- [From RISC-V Cores to Neuromorphic Arrays: A Tutorial on Building Scalable Digital Neuromorphic Processors](https://mlsanity.com/paper/2512.00113/) (2025)

## Abstract (arXiv)

Using Intel's Loihi neuromorphic research chip and ABR's Nengo Deep Learning toolkit, we analyze the inference speed, dynamic power consumption, and energy cost per inference of a two-layer neural network keyword spotter trained to recognize a single phrase. We perform comparative analyses of this keyword spotter running on more conventional hardware devices including a CPU, a GPU, Nvidia's Jetson TX1, and the Movidius Neural Compute Stick. Our results indicate that for this inference application, Loihi outperforms all of these alternatives on an energy cost per inference basis while maintaining equivalent inference accuracy. Furthermore, an analysis of tradeoffs between network size, inference speed, and energy cost indicates that Loihi's comparative advantage over other low-power computing devices improves for larger networks.