Apple's machine learning research team has developed a new multilingual semantic retrieval system for Apple Music search. This system, built on a 305M-parameter bi-encoder fine-tuned from GTE-multilingual-base, significantly improves search recall for misspelled, transliterated, and cross-lingual queries. Deployed globally, the system resulted in a 2.28% conversion rate lift and an 86% reduction in no-result rates, with particularly strong gains for less common "tail" queries. AI
IMPACT Enhances search capabilities for large multilingual datasets, potentially improving user experience and discovery in music streaming services.
RANK_REASON The cluster describes a research paper detailing a new system developed by Apple's ML research team.
Read on arXiv cs.IR (Information Retrieval) →
- alphaXiv
- Apple Music
- arXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- GTE-multilingual-base
- Hugging Face
- ScienceCast
- Vishalaksh Aggarwal
- Kevin Sepúlveda
- Nick Tucey
- Santosh Shankar Rao
- Vivek Kanojiya
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