Mureka Ai Describe Song
Playground
Try it on WavespeedAI!Mureka AI Describe Song is a fast AI music analysis model that describes songs via the official Mureka API. Ready-to-use REST inference API for song description, music analysis, genre and mood understanding, audio metadata workflows, catalog tagging, creative music discovery, and professional music processing with simple integration, no coldstarts, and affordable pricing.
Features
Mureka AI Describe Song
Mureka AI Describe Song analyzes an uploaded audio track and generates a natural-language description of the song. It is suitable for music analysis, genre and mood understanding, metadata enrichment, catalog workflows, and other audio understanding tasks.
Why Choose This?
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Song description workflow Generate a descriptive summary of an uploaded song or music clip.
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Music analysis support Useful for understanding style, instrumentation, mood, arrangement, and overall sonic character.
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Simple audio input Upload a single audio file and get a descriptive analysis without extra configuration.
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Useful for metadata workflows Supports catalog enrichment, content tagging, discovery workflows, and professional music processing pipelines.
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Production-ready API Easy to integrate into music tools, media workflows, and audio analysis systems.
Parameters
| Parameter | Required | Description |
|---|---|---|
| audio | Yes | Input audio track to analyze and describe. |
How to Use
- Upload your audio — provide the song or music clip you want to analyze.
- Submit — run the description request.
- Review the result — use the returned song description in your workflow.
Example Use Case
Upload a music clip to generate a descriptive summary for catalog tagging, playlist curation, or metadata enrichment.
Pricing
Just $0.10 per request.
Billing Rules
- Each description request costs $0.10
- Pricing is fixed per request
Best Use Cases
- Music description — Generate natural-language summaries of songs and audio tracks.
- Genre and mood analysis — Understand the overall feel and style of a track.
- Metadata enrichment — Add descriptive text to music catalogs and media libraries.
- Discovery workflows — Support search, recommendation, and playlist organization.
- Audio analysis pipelines — Use descriptions as part of larger music-processing systems.
Pro Tips
- Upload clear audio for better descriptive results.
- Use the cleanest source clip available when possible.
- Full tracks or representative excerpts usually produce more useful descriptions.
- Avoid heavily distorted, noisy, or very low-quality uploads when accuracy matters.
Notes
audiois required.- Pricing is fixed at $0.10 per request.
- Very noisy, low-quality, or heavily mixed audio may reduce description quality.
Related Models
- Mureka AI Recognize Song — Recognize songs from uploaded audio clips.
- Mureka AI Stem Song — Process songs into stem-based outputs for remixing, editing, and production workflows.
- Mureka AI Generate Lyrics — Generate song lyrics from a prompt.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/mureka-ai/describe-song" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| audio | string | Yes | - | - | Audio URL to describe. Mureka accepts mp3/m4a URLs; this field is mapped to url. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | object | Array of structured result objects. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |