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SAM Audio

Name: SAM Audio
Brand: SAM Audio
Rating: 5 (157 reviews)

Segment any sound with text, visual, or time prompts

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157 Upvotes

About

Meta Segment Anything Model Audio (SAM Audio) is an AI research model from Meta that allows users to accurately separate any sound from any audio or audio-visual source using simple text, visual, or span prompts. It is a state-of-the-art, unified multimodal model capable of isolating general sounds (e.g., traffic, barking), music (instruments, vocals), and speech (speaker isolation, voice separation) from complex mixtures. The model is generative, powered by a flow-matching Diffusion Transformer, and operates in a DAC-VAE latent space. Meta has also released a first-of-its-kind open-source evaluation dataset for prompted audio separation. The technology offers real-world opportunities, particularly for the disabled community and in hearing technology, as highlighted by 2gether-International and Starkey. SAM Audio is part of the broader Segment Anything Model family, which includes SAM 3 for image/video object segmentation and SAM 3D for 3D reconstruction.

Categories & Tags

Open Source Artificial Intelligence Audio #Corporate #Clean #Informative #Minimalist

Color Palette

Background White

#FFFFFF

75%

Text Black/Dark Gray

#000000

15%

Meta Blue (Links/Branding)

#0078FF

Separator Gray

#CCCCCC

Typography

Sans-serif

Headings, Body Text

Design Review

The design of the Meta AI page for SAM Audio is highly corporate, clean, and functional. It adheres to Meta's established branding with a predominantly light theme, utilizing a crisp white background and dark text for excellent readability. The use of Meta Blue for branding elements and interactive links provides clear visual cues and maintains brand consistency. The layout is well-structured with clear headings and bullet points, making the information digestible. The inclusion of images and charts helps to break up text and illustrate concepts effectively. Calls to action like 'Download the model' and 'Try the playground' are prominently displayed. While the content dump shows some repetitive text blocks, assuming a live page would present this more cleanly, the overall aesthetic is professional and user-friendly, prioritizing clear communication of complex technical information.