# LabelBuddy: An Open Source Music and Audio Language Annotation Tagging Tool Using AI Assistance

arXiv: https://arxiv.org/abs/2603.04293 · HTML: https://mlsanity.com/paper/2603.04293/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 15 of its 31 references that are in the map.
- First posted on arXiv 4 Mar 2026.

## Builds on (most cited first, 15 of 15)

- [Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models](https://mlsanity.com/paper/2311.07919/) (2023)
- [PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition](https://mlsanity.com/paper/1912.10211/) (2019)
- [Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models](https://mlsanity.com/paper/2507.08128/) (2025)
- [The VIA Annotation Software for Images, Audio and Video](https://mlsanity.com/paper/1904.10699/) (2019)
- [Adapting Frechet Audio Distance for Generative Music Evaluation](https://mlsanity.com/paper/2311.01616/) (2023)
- [musicnn: Pre-trained convolutional neural networks for music audio tagging](https://mlsanity.com/paper/1909.06654/) (2019)
- [MusicRL: Aligning Music Generation to Human Preferences](https://mlsanity.com/paper/2402.04229/) (2024)
- [MusicEval: A Generative Music Dataset with Expert Ratings for Automatic Text-to-Music Evaluation](https://mlsanity.com/paper/2501.10811/) (2025)
- [Are you really listening? Boosting Perceptual Awareness in Music-QA Benchmarks](https://mlsanity.com/paper/2504.00369/) (2025)
- [Reducing the Annotation Effort for Video Object Segmentation Datasets](https://mlsanity.com/paper/2011.01142/) (2020)
- [audino: A Modern Annotation Tool for Audio and Speech](https://mlsanity.com/paper/2006.05236/) (2020)
- [Ensuring Dataset Quality for Machine Learning Certification](https://mlsanity.com/paper/2011.01799/) (2020)
- [A Survey on Evaluation Metrics for Music Generation](https://mlsanity.com/paper/2509.00051/) (2025)
- [NEAL: An open-source tool for audio annotation](https://mlsanity.com/paper/2212.01457/) (2022)
- [Efficient Bayesian Inference from Noisy Pairwise Comparisons](https://mlsanity.com/paper/2510.09333/) (2025)

## Abstract (arXiv)

The advancement of Machine learning (ML), Large Audio Language Models (LALMs), and autonomous AI agents in Music Information Retrieval (MIR) necessitates a shift from static tagging to rich, human-aligned representation learning. However, the scarcity of open-source infrastructure capable of capturing the subjective nuances of audio annotation remains a critical bottleneck. This paper introduces LabelBuddy, an open-source collaborative auto-tagging audio annotation tool designed to bridge the gap between human intent and machine understanding. Unlike static tools, it decouples the interface from inference via containerized backends, allowing users to plug in custom models for AI-assisted pre-annotation. We describe the system architecture, which supports multi-user consensus, containerized model isolation, and a roadmap for extending agents and LALMs. Code available at https://github.com/GiannisProkopiou/gsoc2022-Label-buddy.