arXiv:2503.18138cs.SDcs.LG2025-03
用音频识别狗狗情绪，准确率超70%
Machine learning based animal emotion classification using audio signals
- 基于音频信号的机器学习方法识别狗的情绪
- 单只狗的音频数据分类准确率超过70%
- 适用于人机交互与情感计算研究
本文提出一种基于机器学习的自动化方法，通过处理和识别音频信号来分类狗的情绪状态。该方法为改善人机交互系统和开发更精确的声学情感分类工具提供了有益信息。所提出的模型在针对单只狗录制的音频信号上实现了超过70%的整体准确率。
原文摘要 · Abstract (English)
This paper presents the machine learning approach to the automated classification of a dog's emotional state based on the processing and recognition of audio signals. It offers helpful information for improving human-machine interfaces and developing more precise tools for classifying emotions from acoustic data. The presented model demonstrates an overall accuracy value above 70% for audio signals recorded for one dog.
情绪识别音频分析机器学习
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