2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.SD2024★ 2 cited
Resource-Efficient Speech Quality Prediction through Quantization Aware Training and Binary Activation Maps
Mattias Nilsson, Riccardo Miccini, Clément Laroche +2
As speech processing systems in mobile and edge devices become more commonplace, the demand for unintrusive speech quality monitoring increases. Deep learning methods provide high-…
cs.LG2024★ 1 cited
Towards a tailored mixed-precision sub-8-bit quantization scheme for Gated Recurrent Units using Genetic Algorithms
Riccardo Miccini, Alessandro Cerioli, Clément Laroche +3
Despite the recent advances in model compression techniques for deep neural networks, deploying such models on ultra-low-power embedded devices still proves challenging. In particu…