Audio for Sports Highlight Detection: A Comparative Empirical Study

arXiv:2609.17923 · cs.CV · Submitted 2026-09-15 · Read on arXiv

cs.CV

Submitted: 2026-09-15

Updated: 2026-09-15

Terminology

• Commentary — 12× in this paper · explained in 2 episodes
• Benchmark — 9× in this paper · explained in 2 episodes
• Transformer — 8× in this paper · explained in 2 episodes
• Grounding — 5× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Calibration — 2× in this paper · explained in 7 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adaptive Multimodal Fusion — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Audio Spectrogram Transformer — 1× in this paper
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Guided attention — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Music Source Separation in the Waveform Domain
• Automated Detection of Sport Highlights from Audio and Video Sources
• AST: Audio Spectrogram Transformer
• TRACE: Temporal Grounding Video LLM via Causal Event Modeling
• Decoupled Weight Decay Regularization
• Deep Learning for Sports Video Event Detection: Tasks, Datasets, Methods, and Challenges

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