TR2026-164

Evaluating Inference-time Algorithms for Semantic Sound Scene Segmentation

    •  Sridhar, S., Wichern, G., Masuyama, Y., Cartwright, M., Le Roux, J., "Evaluating Inference-time Algorithms for Semantic Sound Scene Segmentation", Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), October 2026.
      BibTeX TR2026-164 PDF
      • @inproceedings{Sridhar2026oct2,
      • author = {Sridhar, Sripathi and Wichern, Gordon and Masuyama, Yoshiki and Cartwright, Mark and {Le Roux}, Jonathan},
      • title = {{Evaluating Inference-time Algorithms for Semantic Sound Scene Segmentation}},
      • booktitle = {Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE)},
      • year = 2026,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2026-164}
      • }
  • MERL Contacts:
  • Research Areas:

    Artificial Intelligence, Machine Learning, Speech & Audio

Abstract:

Spatial semantic segmentation of sound scenes (S5) involves the detection and extraction of target sound events in audio files. However, in typical detection-extraction pipelines, errors in the detection module propagate to the extraction module, degrading overall performance. In this work, we develop a multichannel detection-extraction model and evaluate inference-time algorithms to improve the class detection and target sound extraction in a multi-stage setup. We evaluate two fitness functions: binary cross entropy and mixture consistency; two relabeling strategies: naive and conditional confusion matrix relabeling; and three source estimate evaluation models: a multi-label classifier, a fine-tuned single-source classifier, and an off-the-shelf audio judge. We thoroughly evaluate the impact of these design choices on the DCASE 2025 Task
4 dataset, and validate entropy-based gating of inference-time updates on the held-out evaluation set, laying the groundwork for inference-time updates of S5 systems in real-world scenarios.

 

  • Related Publication

  •  Sridhar, S., Wichern, G., Masuyama, Y., Cartwright, M., Le Roux, J., "Evaluating Inference-time Algorithms for Semantic Sound Scene Segmentation", arXiv, October 2026.
    BibTeX arXiv
    • @article{Sridhar2026oct,
    • author = {Sridhar, Sripathi and Wichern, Gordon and Masuyama, Yoshiki and Cartwright, Mark and {Le Roux}, Jonathan},
    • title = {{Evaluating Inference-time Algorithms for Semantic Sound Scene Segmentation}},
    • journal = {arXiv},
    • year = 2026,
    • month = oct,
    • url = {https://arxiv.org/abs/2610.03602}
    • }