COMPARATIVE ANALYSIS OF MODERN COMPONENTS OF INFORMATION TECHNOLOGY FOR SOUND PROCESSING ON ROBOTIC SYSTEMS
DOI:
https://doi.org/10.30888/2663-5712.2026-35-01-083Keywords:
artificial intelligence, robotic systems, sound information, information processing, cloud service, mathematical modelsAbstract
The paper examines the current state and possibilities of processing information flows in modern robotic systems with artificial intelligence tools. Comparative characteristics of components of various systems and technologies are presented to assess theReferences
Steven W. Smith. The Scientist and Engineer's Guide to Digital Signal Processing / Audio Processing. Chapter 22. - Р. 353-372. URL: https://www.analog.com/media/en/technical-documentation/dsp-book/dsp_book_Ch22.pdf
Environmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices. arXiv preprint. 2021. URL: https://arxiv.org/abs/2103.03483
TensorFlow. Transfer Learning for Audio Recognition. URL: https://www.tensorflow.org/tutorials/audio/transfer_learning_audio
STMicroelectronics. STM32 AI Model Zoo. URL: https://github.com/STMicroelectronics/stm32ai-modelzoo
EfficientAT: GitHub Repository. URL: https://github.com/fschmid56/EfficientAT
Efficient Large-Scale Audio Tagging via Transformer-to-CNN Knowledge Distillation. arXiv preprint. 2023. URL: https://arxiv.org/abs/2310.15648
ESC-NAS: Environment Sound Classification Using Hardware-Aware Neural Architecture Search for the Edge. Sensors. 2024. URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC11207705/
BEATs: Audio Pre-Training with Acoustic Tokenizers. arXiv preprint. 2022. URL: https://arxiv.org/abs/2212.09058
EAT: Self-Supervised Pre-Training with Efficient Audio Transformer. arXiv preprint. 2024. URL: https://arxiv.org/abs/2401.03497
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition. arXiv preprint. 2019. URL: https://arxiv.org/abs/1912.10211
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
