Make the audio similarity engine the default one for new installs, if available
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@@ -42,8 +42,8 @@ _LMS_ provides several ways to help you find the music you like:
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* ...
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__Note__: the recommendation engine supports two modes:
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* **Audio similarity** (default): uses MusicNN embeddings. Extraction throughput depends heavily on both the number of scanner threads and the speed of your storage. Typical reported speeds range from ~1k tracks/hour on a Raspberry Pi 4 to ~25k tracks/hour on an Intel Core i5-13500.
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* **Tag-based**: uses metadata tags `genre`, `mood`, `grouping`, and `language`.
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* **Audio similarity**: uses MusicNN embeddings. Extraction throughput depends heavily on both the number of scanner threads and the speed of your storage. Typical reported speeds range from ~1k tracks/hour on a Raspberry Pi 4 (3 threads) to ~25k tracks/hour on an Intel Core i5-13500 (10 threads). To speed up extraction, consider tweaking `scanner-thread-count` in `lms.conf` (defaults to half the number of logical CPUs).
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## About tags
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_LMS_ primarily relies on tags to organize your music collection but also supports browsing by directory using the [Subsonic/OpenSubsonic API](SUBSONIC.md).
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