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Finetuning Strategies for Querying Sounds by Vocal Imitation
One-line summary
An AI research paper on Finetuning Strategies for Querying Sounds by Vocal Imitation.
Engineering notes
Engineering notes will be added by the aipentium editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。
Original abstract
This technical report describes our winning submission to the AES AIMLA 2025 Challenge on querying sound effects by vocal imitation. We investigate two complementary fine-tuning strategies: contrastive learning with a frozen, pretrained CED encoder, and joint contrastive-triplet learning with semi-hard negatives using a MobileNetV3 encoder. This report has been updated for posterity to include details released after the challenge.
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