Aud-Sur: An Audio Analyzer Assistant for Audio Surveillance Applications
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866908291820421120 |
|---|---|
| author | Lam, Phat Pham, Lam Tran, Dat Schindler, Alexander Poletti, Silvia Hasenbalg, Marcel Fischinger, David Boyer, Martin |
| author_facet | Lam, Phat Pham, Lam Tran, Dat Schindler, Alexander Poletti, Silvia Hasenbalg, Marcel Fischinger, David Boyer, Martin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_23827 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Aud-Sur: An Audio Analyzer Assistant for Audio Surveillance Applications Lam, Phat Pham, Lam Tran, Dat Schindler, Alexander Poletti, Silvia Hasenbalg, Marcel Fischinger, David Boyer, Martin Audio and Speech Processing 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. |
| title | Aud-Sur: An Audio Analyzer Assistant for Audio Surveillance Applications |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2503.23827 |