TrackRate user guide
Metric Lens
Filter a TrackRate library by measured sound, explore metric ranges, and find tracks near a seed track.
5 questions
What is Metric Lens, and what do I need before using it?
Metric Lens is a Premium filter for selecting tracks by measured audio characteristics rather than only by metadata. Run Calculate Metrics first so TrackRate has the required analysis values. Tracks without a selected metric cannot be placed accurately in its range.
Use it when words such as genre or mood are too broad—for example, to find the calmer part of an electronic collection, brighter tracks within jazz, or songs with similar rhythmic and spectral behavior.
How do I use the Metric Lens Range Explorer?
Open Metric Lens, select a metric, and adjust the minimum and maximum handles. The current library pool is narrowed to tracks whose value lies inside that interval. Add ordinary chips, ratings, or tags first when the range should operate on a specific collection.
Start with genre:electronic, year:>=2018, and ratings 7–10. Then select an energy-related metric and keep its middle-to-high range. The result is a recent, well-rated electronic pool with a more consistent sound profile.
What is Metric Neighborhood, and how is it different from a range?
A range asks for tracks between chosen numeric limits. Metric Neighborhood starts from a reference track and finds nearby tracks across selected measurements. It is useful when you can identify one song that has the desired sound but cannot describe that sound with metadata.
Select a reference track, choose the relevant metrics, and adjust the neighborhood size. Add a tag or folder filter when similarity should stay inside a particular context, such as #ambient or a DJ crate.
Which metrics should I choose for a practical similarity search?
Choose measurements that describe the difference you actually care about. Rhythm-oriented metrics help with pulse and transition continuity; loudness and energy measurements help shape intensity; spectral measurements help distinguish bright, dense, dark, or sparse material. Derivative scores combine several raw measurements into more convenient musical dimensions.
Begin with two or three metrics rather than all of them. Compare the result, then add one measurement at a time. Too many strict dimensions can leave very few neighbors and make it difficult to understand why a track was selected.
Why does Metric Lens show too few tracks or inconsistent results?
Check that analysis has completed for the candidate files and that other filters are not already restrictive. A narrow metric interval combined with an artist, year, tag, rating, and format filter may leave no valid tracks even though every setting works independently.
Reset Metric Lens, verify the ordinary filtered pool, then introduce one metric with a broad range. Narrow it gradually. For neighborhood searches, reduce the number of chosen metrics or increase the neighborhood size.
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