# Emotions Beyond Words: Non-Speech Audio Emotion Recognition With Edge Computing

arXiv: https://arxiv.org/abs/2305.00725 · HTML: https://mlsanity.com/paper/2305.00725/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 May 2023.

## Built on by (most cited first, 1 of 1)

- [Transformer Redesign for Late Fusion of Audio-Text Features on Ultra-Low-Power Edge Hardware](https://mlsanity.com/paper/2510.18036/) (2025)

## Abstract (arXiv)

Non-speech emotion recognition has a wide range of applications including healthcare, crime control and rescue, and entertainment, to name a few. Providing these applications using edge computing has great potential, however, recent studies are focused on speech-emotion recognition using complex architectures. In this paper, a non-speech-based emotion recognition system is proposed, which can rely on edge computing to analyse emotions conveyed through non-speech expressions like screaming and crying. In particular, we explore knowledge distillation to design a computationally efficient system that can be deployed on edge devices with limited resources without degrading the performance significantly. We comprehensively evaluate our proposed framework using two publicly available datasets and highlight its effectiveness by comparing the results with the well-known MobileNet model. Our results demonstrate the feasibility and effectiveness of using edge computing for non-speech emotion detection, which can potentially improve applications that rely on emotion detection in communication networks. To the best of our knowledge, this is the first work on an edge-computing-based framework for detecting emotions in non-speech audio, offering promising directions for future research.