mlsanityData to 7 Oct 2026

The NTT DCASE2020 Challenge Task 6 system: Automated Audio Captioning with Keywords and Sentence Length Estimation

arXiv 2007.00225 ↗First posted 1 Jul 2020eess.AS cs.LG cs.SDcited by 8

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Abstract (arXiv)

This technical report describes the system participating to the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge, Task 6: automated audio captioning. Our submission focuses on solving two indeterminacy problems in automated audio captioning: word selection indeterminacy and sentence length indeterminacy. We simultaneously solve the main caption generation and sub indeterminacy problems by estimating keywords and sentence length through multi-task learning. We tested a simplified model of our submission using the development-testing dataset. Our model achieved 20.7 SPIDEr score where that of the baseline system was 5.4.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Jul 2020.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 2; 2024: 0; 2025: 1.

8 papers.