cs.SD · 2026-08-04 · No. 74

Sound, 2026-08-04.

2 new papers in cs.SD. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Can Foundation Models Hear What Made That Sound? A Tiered Benchmark of Audio-Language Models and Traditional Classifiers for Closed-Set Sound Source Identification

    Sajjad Abdoli, Ghassan Al-Sumaidaee, Ahmad ElShiekh, Ahmed Rashad

    cs.SD · cs.AI

    We benchmark eleven audio classification methods: five task-aware closed-set LLMs (four Gemini models plus open-weight Kimi-Audio-7B-Instruct), four fixed-vocabulary taggers (YAMNet, PANNs, Whisper-AT, and SSLAM), a zero-shot audio-text model (CLAP), and an audio-grounded LLM (BAT). We evaluate them on a closed-set sound-source identification task over 2,242 clips spanning 23 fine-grained classes and 11 categories. Since these methods differ...

    arxiv.org/abs/2608.02397 · PDF

  2. 02

    Uncertainty-Aware Crossmodal Fusion for Classification of Animal Behavior

    Ehsan Yaghoubi, Florian Haselbeck

    cs.SD · cs.AI

    Artificial intelligence offers substantial potential for acoustic monitoring of animals, from welfare assessment in precision livestock farming to wildlife conservation and ecological research, where vocalizations can indicate health, stress, and social states earlier and at lower cost than manual observation. However, recordings in these settings are obtained under uncontrolled conditions, including environmental noise, reverberation,...

    arxiv.org/abs/2608.02104 · PDF

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