# Aud-Sur: An Audio Analyzer Assistant for Audio Surveillance Applications

arXiv: https://arxiv.org/abs/2503.23827 · HTML: https://mlsanity.com/paper/2503.23827/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2025.

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

- [Shared Representation Learning for Reference-Guided Targeted Sound Detection](https://mlsanity.com/paper/2603.17025/) (2026)

## Abstract (arXiv)

In this paper, we present an audio analyzer assistant tool designed for a wide range of audio-based surveillance applications (This work is a part of our DEFAME FAKES and EUCINF projects). The proposed tool, refered to as Aud-Sur, comprises two main phases Audio Analysis and Audio Retrieval, respectively. In the first phase, multiple open-source audio models are leveraged to extract information from input audio recording uploaded by a user. In the second phase, users interact with the Aud-Sur tool via a natural question-and-answer manner, powered by a large language model (LLM), to retrieve the information extracted from the processed audio file. The Aud-Sur tool was deployed using Docker on a microservices-based architecture design. By leveraging open-source audio models for information extraction, LLM for audio information retrieval, and a microservices-based deployment approach, the proposed Aud-Sur tool offers a highly extensible and adaptable framework that can integrate more audio tasks, and be widely shared within the audio community for further development.