Résultats de recherche

Today, transformer and conformer models are commonly used in end-to-end speech recognition. Generally, conformer models are more efficient than transformers, but both suffer from large sizes, and expensive computing cost making their use environmentally unfriendly. In this paper, we propose compressing these models using quantization and pruning, evaluating size and computing time improvements while monitoring […]

Due to advancements in sensing technologies, enhanced IoT architectures, and expanded connectivity options, predictive maintenance has emerged as a compelling solution within the context of Industry 4.0 for industrial systems. However, within this landscape, such as in Smart Buildings (SBs), the lack of failure data poses a significant challenge for implementing traditional data-based approaches documented […]