← Search

Francesco Calivá

2 accepted papers

2023

Fixed-Point Quantization Aware Training for on-Device Keyword-Spotting

ICASSP 2023accepted

Fixed-point (FXP) inference has proven suitable for embedded devices with limited computational resources, and yet model training is continually performed in floating-point (FLP). FXP training has not been fully explored and the non-trivial conversion from FLP to FXP presents unavoidable performance…

Cited by 0SourceScholar
2023

Self-Supervised Speech Representation Learning for Keyword-Spotting With Light-Weight Transformers

ICASSP 2023accepted

Self-supervised speech representation learning (S3RL) is revolutionizing the way we leverage the ever-growing availability of data. While S3RL related studies typically use large models, we employ light-weight networks to comply with tight memory of compute-constrained devices. We demonstrate the ef…

Cited by 0SourceScholar