Conjoint Audio-to-Spikes Encoding and Processing for Efficient Neuromorphic Speech Recognition
cs.NE, cs.AI, cs.LG, eess.AS
Submitted: 2026-08-31
Updated: 2026-08-31
Terminology
Sources
- V2CE: Video to Continuous Events Simulator
- Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
- Fundamental Survey on Neuromorphic Based Audio Classification
- P-SpikeSSM: Harnessing Probabilistic Spiking State Space Models for Long-Range Dependency Tasks
- Efficient Speech Command Recognition Leveraging Spiking Neural Network and Curriculum Learning-based Knowledge Distillation
- Evaluation of Neuromorphic Spike Encoding of Sound Using Information Theory
- Efficient spike encoding algorithms for neuromorphic speech recognition
- The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks
- Adam: A Method for Stochastic Optimization
- Choice of Mel Filter Bank in Computing MFCC of a Resampled Speech
- Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation
- DelRec: learning delays in recurrent spiking neural networks
- SiLIF: Structured State Space Model Dynamics and Parametrization for Spiking Neural Networks
- ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network
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