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29:Td3e,# SAM-Audio: Audio Source Separation Model

## What is SAM-Audio?
SAM-Audio is a foundation AI model from Meta designed for **audio source separation**: isolating a target sound (like â€œdrumsâ€, â€œspeechâ€, or â€œsirenâ€) from a mixed recording. Instead of separating only fixed stems, SAM-Audio aims to **segment any sound** you describe, making it useful for modern audio editing pipelines, sound event detection, and multimedia analysis.

On Segmind, you provide an audio input and a **sound description prompt**. The model returns an isolated track containing the requested source, enabling workflows like â€œextract vocals from a songâ€, â€œremove background noiseâ€, or â€œpull out footsteps from a sceneâ€.

## Key Features
- **Prompted sound isolation** using natural language text (e.g., â€œkeyboard typingâ€, â€œfemale narrationâ€).
- **Fine-grained separation** for complex mixes (music, ambience, dialogue + effects).
- **Developer-friendly inputs**: audio via URL or Base64, with selectable output format.
- **Quality tuning** with reranking to improve the best-candidate separation.
- **Strong fit for automated pipelines** (moderation, indexing, annotation, post-production).

## Best Use Cases
- **Audio editing & post-production**: isolate dialogue, ambience, SFX, instruments.
- **Content creation**: remixing, stem-like extraction, cleaner voiceovers.
- **Sound event detection**: extract target events before classification or labeling.
- **Multimedia & video analysis**: separate scene sounds for search and retrieval.
- **Accessibility**: enhance speech tracks for transcription and captioning.

## Prompt Tips and Output Quality
- Be **specific**: â€œsnare drum hitsâ€ often separates better than â€œdrumsâ€.
- Include **context**: â€œcrowd cheering in a stadiumâ€ vs. â€œcheeringâ€.
- If multiple similar sources exist, add qualifiers: â€œlead vocalâ€, â€œbackground chatterâ€.
- Use `output_format: wav` for highest fidelity; `mp3` for smaller files.
- Increase `reranking_candidates` (1â€“8) when the separation is close but imperfect; higher values typically improve selection at the cost of more computation.

**Core parameters**
- `audio` (required): URL/Base64 for the input audio.
- `description` (required): the sound to isolate.
- `output_format` (optional): `wav` or `mp3` (default `wav`).
- `reranking_candidates` (optional, advanced): candidate count (default `4`).

## FAQs
**Is SAM-Audio open-source?**  
Meta publishes research assets for SAM-Audio, but licensing and usage terms may vary by distribution. Check the upstream repository/terms for your deployment scenario.

**How is SAM-Audio different from stem splitters (vocals/drums/bass)?**  
Itâ€™s **prompt-driven**: you can target *any* described sound, not only fixed music stems.

**What should I put in `description` for best results?**  
Use a concise noun phrase plus qualifiers (instrument, source, environment), e.g., â€œmale speech in a carâ€, â€œdog barkingâ€, â€œhi-hat patternâ€.

**Should I choose WAV or MP3 output?**  
Choose **WAV** for editing and evaluation; choose **MP3** for lightweight previews and distribution.

**What does `reranking_candidates` do?**  
It controls how many separation candidates are generated and reranked; increasing it can improve the final isolated track when prompts are ambiguous.2a:T935,# SAM-Audio: Audio Source Separation Model

Unlock prompt-driven sound isolation for music production, post-production, content creation, and analysis.

## Quick Start
1. **Prepare Input**  
   â€¢ `audio`: URL or Base64 of your mixed track (e.g., `https://.../office.mp4`).  
   â€¢ `description`: concise noun phrase (e.g., â€œsnare hitsâ€, â€œfemale narrationâ€).  
2. **Choose Output**  
   â€¢ `output_format`: `wav` (highest fidelity) or `mp3` (smaller footprint).  
3. **Adjust Quality**  
   â€¢ `reranking_candidates` (1â€“8, default 4): more candidates increase separation quality at cost of compute.

## Core Parameters
```json
{
  "audio": "...",              
  "description": "drums",      
  "output_format": "wav",      
  "reranking_candidates": 4    
}
```

## Recommended Settings by Use Case

- **Podcast & Voiceovers**  
  â€¢ description: â€œmale speech in studioâ€  
  â€¢ output_format: wav  
  â€¢ reranking_candidates: 3 (fast) or 5 (cleaner)  

- **Music Remix & Stems**  
  â€¢ description: â€œlead vocalsâ€, â€œhi-hat grooveâ€  
  â€¢ output_format: wav  
  â€¢ reranking_candidates: 6â€“8  

- **Sound Effects for Video**  
  â€¢ description: â€œfootsteps on gravelâ€, â€œthunderstorm ambienceâ€  
  â€¢ output_format: mp3 (preview) or wav (final)  
  â€¢ reranking_candidates: 4  

- **Noise Reduction & Forensics**  
  â€¢ description: â€œcar engine noiseâ€, â€œairplane cabin humâ€  
  â€¢ output_format: wav  
  â€¢ reranking_candidates: 7â€“8  

- **Event Detection Preprocessing**  
  â€¢ description: â€œdog barkingâ€, â€œgunshotâ€  
  â€¢ output_format: mp3  
  â€¢ reranking_candidates: 2â€“4  

## Tips & Best Practices
- Be **specific**: â€œsnare drum hitsâ€ vs. â€œdrumsâ€.  
- Add **context**: â€œcrowd cheering in stadiumâ€ improves focus.  
- Qualify overlaps: â€œbackground chatterâ€ vs. â€œlead dialogueâ€.  
- Preview with `mp3`, finalize in `wav`.  
- Increase `reranking_candidates` only if output artifacts persist.

## Troubleshooting
- **Artifact speckles**: lower candidates or revise description.  
- **Missing detail**: raise candidates to 6â€“8.  
- **Slow runtime**: use candidates 2â€“4.

Leverage SAM-Audioâ€™s promptable interface for bespoke audio pipelinesâ€” from automated indexing to professional post-production.1e:["$","$L28",null,{"route":"sam-audio-large","modelDetails":{"title":"Sam Audio Large","thumbnail_image":"https://segmind-resources.s3.amazonaws.com/output/sam-audio-large-9606.png","type":"textToAudio","model_type":"SS","is_depreciated":false,"meta_description":"Isolates any described sound from mixed audio for enhanced editing and analysis.","seo_description":"$29","guide":"$2a","pricing_guide":null,"artifacts":[],"default_image_output":"https://segmind-inference-io.s3.amazonaws.com/sam-audio/e5278202c7a8aa6cddb9090840b5a581/target_9437e7fe38d64db386157f0284fbf861.wav","default_response":null,"parameters":{"audio":{"isRequired":true,"affectsPricing":false,"type":"str","description":"Audio file URL or base64 to separate into components.","isEnum":false,"hidden":false,"isAdvanced":false,"displayOrder":0,"component":"textarea","format":"uri","displayValue":"https://segmind-resources.s3.amazonaws.com/input/05f46d53-2089-473b-be52-c054174952dd-sample_input.mp3","label":"Audio Input (URL or Base64)"},"description":{"isRequired":true,"affectsPricing":false,"type":"str","description":"Describe the sound to isolate, e.g., drums or vocals.","isEnum":false,"hidden":false,"isAdvanced":false,"displayOrder":1,"component":"textarea","displayValue":"a man speaking","label":"Sound Description"},"output_format":{"isRequired":false,"affectsPricing":false,"type":"str","description":"Output audio format. WAV for quality, MP3 for smaller size.","isEnum":true,"hidden":false,"isAdvanced":false,"displayOrder":2,"component":"dropdown","displayValue":"wav","label":"Output Format","values":["wav","mp3"],"default":"wav"},"reranking_candidates":{"isRequired":false,"affectsPricing":false,"type":"int","description":"Number of separation candidates. Higher values improve quality.","isEnum":false,"hidden":false,"isAdvanced":true,"displayOrder":3,"component":"slider","displayValue":4,"label":"Reranking Candidates","range":[1,8],"step":1,"default":1}},"endpoints":{"main":"/v1/sam-audio-large"},"api_notes":[],"model_outputs":null,"llm_capabilities":null,"license":"","github_link":null,"inference_provider":"SEGMIND_SERVERLESS","created_ts":"2026-02-27 12:00:28.447800+00:00","slug":"sam-audio-large","name":"Sam Audio Large","description":"Isolate any described sound from mixed audio tracks.","category":"textToAudio","modality":"audio","input":"text","output":"audio","provider":"META","thumbnail_url":"https://segmind-resources.s3.amazonaws.com/output/sam-audio-large-9606.png","is_new":false,"coming_soon":false,"popularity_score":49,"category_percentile":87,"average_cost":0.07554795314285716,"latency_seconds":17.56929,"created_at":"2026-02-27 12:00:28.447800+00:00","parameters_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","type":"object","properties":{"audio":{"type":"string","format":"uri","x-file-metadata":{"allowed-types":["audio/*"]},"title":"Audio Input (URL or Base64)","description":"Audio file URL or base64 to separate into components.","x-ui-metadata":{"order":0,"advanced":false,"hidden":false}},"description":{"type":"string","title":"Sound Description","description":"Describe the sound to isolate, e.g., drums or vocals.","x-ui-metadata":{"order":1,"advanced":false,"hidden":false}},"output_format":{"type":"string","title":"Output Format","description":"Output audio format. WAV for quality, MP3 for smaller size.","oneOf":[{"const":"wav","title":"wav"},{"const":"mp3","title":"mp3"}],"default":"wav","x-ui-metadata":{"order":2,"advanced":false,"hidden":false}},"reranking_candidates":{"type":"integer","title":"Reranking Candidates","description":"Number of separation candidates. Higher values improve quality.","minimum":1,"maximum":8,"default":1,"x-ui-metadata":{"order":3,"advanced":true,"hidden":false}}},"required":["audio","description"],"examples":[{"audio":"https://segmind-resources.s3.amazonaws.com/input/05f46d53-2089-473b-be52-c054174952dd-sample_input.mp3","description":"a man speaking","output_format":"wav","reranking_candidates":4}]}},"metrics":{"total_requests":null,"latency":17.56929},"children":"$L2b"}]
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2d:T558,{"@context":"https://schema.org","@type":"FAQPage","@id":"https://www.segmind.com/models/sam-audio-large#faq","mainEntity":[{"@type":"Question","name":"Is SAM-Audio open-source?","acceptedAnswer":{"@type":"Answer","text":"Meta publishes research assets for SAM-Audio, but licensing and usage terms may vary by distribution. Check the upstream repository/terms for your deployment scenario."}},{"@type":"Question","name":"How is SAM-Audio different from stem splitters (vocals/drums/bass)?","acceptedAnswer":{"@type":"Answer","text":"Itâ€™s prompt-driven: you can target any described sound, not only fixed music stems."}},{"@type":"Question","name":"What should I put in `description` for best results?","acceptedAnswer":{"@type":"Answer","text":"Use a concise noun phrase plus qualifiers (instrument, source, environment), e.g., â€œmale speech in a carâ€, â€œdog barkingâ€, â€œhi-hat patternâ€."}},{"@type":"Question","name":"Should I choose WAV or MP3 output?","acceptedAnswer":{"@type":"Answer","text":"Choose WAV for editing and evaluation; choose MP3 for lightweight previews and distribution."}},{"@type":"Question","name":"What does `reranking_candidates` do?","acceptedAnswer":{"@type":"Answer","text":"It controls how many separation candidates are generated and reranked; increasing it can improve the final isolated track when prompts are ambiguous."}}]}2f:Td3e,# SAM-Audio: Audio Source Separation Model

## What is SAM-Audio?
SAM-Audio is a foundation AI model from Meta designed for **audio source separation**: isolating a target sound (like â€œdrumsâ€, â€œspeechâ€, or â€œsirenâ€) from a mixed recording. Instead of separating only fixed stems, SAM-Audio aims to **segment any sound** you describe, making it useful for modern audio editing pipelines, sound event detection, and multimedia analysis.

On Segmind, you provide an audio input and a **sound description prompt**. The model returns an isolated track containing the requested source, enabling workflows like â€œextract vocals from a songâ€, â€œremove background noiseâ€, or â€œpull out footsteps from a sceneâ€.

## Key Features
- **Prompted sound isolation** using natural language text (e.g., â€œkeyboard typingâ€, â€œfemale narrationâ€).
- **Fine-grained separation** for complex mixes (music, ambience, dialogue + effects).
- **Developer-friendly inputs**: audio via URL or Base64, with selectable output format.
- **Quality tuning** with reranking to improve the best-candidate separation.
- **Strong fit for automated pipelines** (moderation, indexing, annotation, post-production).

## Best Use Cases
- **Audio editing & post-production**: isolate dialogue, ambience, SFX, instruments.
- **Content creation**: remixing, stem-like extraction, cleaner voiceovers.
- **Sound event detection**: extract target events before classification or labeling.
- **Multimedia & video analysis**: separate scene sounds for search and retrieval.
- **Accessibility**: enhance speech tracks for transcription and captioning.

## Prompt Tips and Output Quality
- Be **specific**: â€œsnare drum hitsâ€ often separates better than â€œdrumsâ€.
- Include **context**: â€œcrowd cheering in a stadiumâ€ vs. â€œcheeringâ€.
- If multiple similar sources exist, add qualifiers: â€œlead vocalâ€, â€œbackground chatterâ€.
- Use `output_format: wav` for highest fidelity; `mp3` for smaller files.
- Increase `reranking_candidates` (1â€“8) when the separation is close but imperfect; higher values typically improve selection at the cost of more computation.

**Core parameters**
- `audio` (required): URL/Base64 for the input audio.
- `description` (required): the sound to isolate.
- `output_format` (optional): `wav` or `mp3` (default `wav`).
- `reranking_candidates` (optional, advanced): candidate count (default `4`).

## FAQs
**Is SAM-Audio open-source?**  
Meta publishes research assets for SAM-Audio, but licensing and usage terms may vary by distribution. Check the upstream repository/terms for your deployment scenario.

**How is SAM-Audio different from stem splitters (vocals/drums/bass)?**  
Itâ€™s **prompt-driven**: you can target *any* described sound, not only fixed music stems.

**What should I put in `description` for best results?**  
Use a concise noun phrase plus qualifiers (instrument, source, environment), e.g., â€œmale speech in a carâ€, â€œdog barkingâ€, â€œhi-hat patternâ€.

**Should I choose WAV or MP3 output?**  
Choose **WAV** for editing and evaluation; choose **MP3** for lightweight previews and distribution.

**What does `reranking_candidates` do?**  
It controls how many separation candidates are generated and reranked; increasing it can improve the final isolated track when prompts are ambiguous.30:T935,# SAM-Audio: Audio Source Separation Model

Unlock prompt-driven sound isolation for music production, post-production, content creation, and analysis.

## Quick Start
1. **Prepare Input**  
   â€¢ `audio`: URL or Base64 of your mixed track (e.g., `https://.../office.mp4`).  
   â€¢ `description`: concise noun phrase (e.g., â€œsnare hitsâ€, â€œfemale narrationâ€).  
2. **Choose Output**  
   â€¢ `output_format`: `wav` (highest fidelity) or `mp3` (smaller footprint).  
3. **Adjust Quality**  
   â€¢ `reranking_candidates` (1â€“8, default 4): more candidates increase separation quality at cost of compute.

## Core Parameters
```json
{
  "audio": "...",              
  "description": "drums",      
  "output_format": "wav",      
  "reranking_candidates": 4    
}
```

## Recommended Settings by Use Case

- **Podcast & Voiceovers**  
  â€¢ description: â€œmale speech in studioâ€  
  â€¢ output_format: wav  
  â€¢ reranking_candidates: 3 (fast) or 5 (cleaner)  

- **Music Remix & Stems**  
  â€¢ description: â€œlead vocalsâ€, â€œhi-hat grooveâ€  
  â€¢ output_format: wav  
  â€¢ reranking_candidates: 6â€“8  

- **Sound Effects for Video**  
  â€¢ description: â€œfootsteps on gravelâ€, â€œthunderstorm ambienceâ€  
  â€¢ output_format: mp3 (preview) or wav (final)  
  â€¢ reranking_candidates: 4  

- **Noise Reduction & Forensics**  
  â€¢ description: â€œcar engine noiseâ€, â€œairplane cabin humâ€  
  â€¢ output_format: wav  
  â€¢ reranking_candidates: 7â€“8  

- **Event Detection Preprocessing**  
  â€¢ description: â€œdog barkingâ€, â€œgunshotâ€  
  â€¢ output_format: mp3  
  â€¢ reranking_candidates: 2â€“4  

## Tips & Best Practices
- Be **specific**: â€œsnare drum hitsâ€ vs. â€œdrumsâ€.  
- Add **context**: â€œcrowd cheering in stadiumâ€ improves focus.  
- Qualify overlaps: â€œbackground chatterâ€ vs. â€œlead dialogueâ€.  
- Preview with `mp3`, finalize in `wav`.  
- Increase `reranking_candidates` only if output artifacts persist.

## Troubleshooting
- **Artifact speckles**: lower candidates or revise description.  
- **Missing detail**: raise candidates to 6â€“8.  
- **Slow runtime**: use candidates 2â€“4.

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