AIBA: Attention-based Instrument Band Alignment for Text-to-Audio Diffusion
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866909805851967488 |
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| author | Koh, Junyoung Kim, Soo Yong Choi, Gyu Hyeong Choi, Yongwon |
| author_facet | Koh, Junyoung Kim, Soo Yong Choi, Gyu Hyeong Choi, Yongwon |
| contents | We present AIBA (Attention-In-Band Alignment), a lightweight, training-free pipeline to quantify where text-to-audio diffusion models attend on the time-frequency (T-F) plane. AIBA (i) hooks cross-attention at inference to record attention probabilities without modifying weights; (ii) projects them to fixed-size mel grids that are directly comparable to audio energy; and (iii) scores agreement with instrument-band ground truth via interpretable metrics (T-F IoU/AP, frequency-profile correlation, and a pointing game). On Slakh2100 with an AudioLDM2 backbone, AIBA reveals consistent instrument-dependent trends (e.g., bass favoring low bands) and achieves high precision with moderate recall. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_20891 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AIBA: Attention-based Instrument Band Alignment for Text-to-Audio Diffusion Koh, Junyoung Kim, Soo Yong Choi, Gyu Hyeong Choi, Yongwon Sound We present AIBA (Attention-In-Band Alignment), a lightweight, training-free pipeline to quantify where text-to-audio diffusion models attend on the time-frequency (T-F) plane. AIBA (i) hooks cross-attention at inference to record attention probabilities without modifying weights; (ii) projects them to fixed-size mel grids that are directly comparable to audio energy; and (iii) scores agreement with instrument-band ground truth via interpretable metrics (T-F IoU/AP, frequency-profile correlation, and a pointing game). On Slakh2100 with an AudioLDM2 backbone, AIBA reveals consistent instrument-dependent trends (e.g., bass favoring low bands) and achieves high precision with moderate recall. |
| title | AIBA: Attention-based Instrument Band Alignment for Text-to-Audio Diffusion |
| topic | Sound |
| url | https://arxiv.org/abs/2509.20891 |