The Tool Desk
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Cwalo’s All-In-One-Music-Structure-Analysis model on Replicate takes an audio file and estimates its tempo, beats, downbeats, song-section boundaries, and section labels. You can try it on Replicate’s hosted model page or call it through the API; optional settings can also produce visualizations, sonifications, embeddings, activations, and demixed audio files.
What the model analyzes
The model combines rhythmic timing with song-level structure. Its listed outputs include tempo in beats per minute (BPM), beat and downbeat timings, functional segment boundaries, and labels such as intro, verse, chorus, bridge, and outro. It can also separate audio into drums, bass, vocals, and other.
The Replicate implementation offers optional demixed audio exports. The model page also lists controls for saving visualizations, sonifications, activations, and embeddings, along with a model-selection field whose displayed default is harmonix-all. These are output and configuration options, not switches that promise more accurate analysis. The available inputs and their current defaults are shown in the Replicate model page.
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Use the hosted page
- Open the Cwalo model page and use its playground to provide an audio file and review the available settings.
- Enable only the additional artifacts you need. For example, request demixed audio only if you want separate source files, or a visualization if you want a visual representation of an analysis.
- Start the run, then inspect the returned results and any media files. Treat the timings and labels as predictions and listen to the track around the proposed boundaries.
Call the API
The Replicate HTTP API documentation describes how to submit a prediction and retrieve its output. API use requires a Replicate token. You can provide audio as a hosted URL, use a local file through a client library, or pass a base64 data URI. Replicate recommends the data-URI approach only for files under 1 MB.
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- Follow the API guide to authenticate with your token and submit a prediction using the model’s current input schema.
- Provide the audio using an input method supported by the API and select the optional outputs you need.
- Read the returned JSON and follow the output file URLs. The API guide shows how to access file URLs and write output files locally.
The reviewed documentation does not establish a complete list of accepted audio formats or a maximum duration. Check the model’s current schema before building an automated workflow, and test with a representative file.
Choose outputs based on your goal
- Tempo, beats, and downbeats: useful when you need rhythmic timing estimates.
- Segment boundaries and functional labels: useful for exploring a track’s likely sections, such as verses and choruses.
- Demixed audio: request this when you need separate drums, bass, vocals, and other outputs.
- Visualizations, sonifications, embeddings, and activations: optional artifacts for inspecting or using the analysis in other workflows. Their presence does not itself establish that the predictions are better.
Requesting extra artifacts may affect resource use. The model listing gives an approximate cost of $0.12 per run (about eight runs per dollar) and a typical completion time of around 126 seconds on Nvidia L40S hardware, while noting that both vary with inputs. These are live-service estimates, not fixed guarantees; check the current listing before budgeting or estimating turnaround.
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How to interpret the results
Use the returned timing points and labels as a starting point, not as ground truth. Check whether a proposed boundary falls where the music actually changes, and whether a label fits the track. The reviewed sources do not establish accuracy across every genre, recording condition, or individual song.
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| Reported measure | All-In-One result in the paper |
|---|---|
| Beat F1 | 0.958 |
| Downbeat F1 | 0.915 |
| Segment HR.5F | 0.660 |
| Functional-label PWF | 0.738 |
| Model parameters | About 300,000 |
These figures describe the paper’s evaluated model on its stated dataset and protocol. They do not guarantee performance on your audio or prove that every deployed version and configuration produces identical results.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Hosted use or local execution?
Replicate is the more direct route for a beginner who wants to try an analysis without setting up the model locally. The implementation repository also documents running it with Cog and Docker, including GPU recommendations. It notes that CPU operation is possible with a changed configuration but may be considerably slower, particularly for longer files. See the Cwalo implementation repository for its local execution details.
Quick Recap
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