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🔉 Introducing SAM Audio, the first unified model that isolates any sound from complex audio mixtures using text, visual, or span prompts. We’re sharing SAM Audio with the community, along with a perception encoder model, benchmarks and research papers, to empower others to explore new forms of expression and... show more

AI at Meta

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1,251,615 views • 8 months ago •via X (Twitter)

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Introducing SAM Audio: the first unified AI model that allows you to isolate and edit sound from complex audio mixtures. This could mean isolating the guitar in a video of your band, filtering out traffic noises, or removing the sound of a dog barking in your podcast, all with text, visual, and time span prompts.

Introducing SAM Audio: the first unified AI model that allows you to isolate and edit sound from complex audio mixtures. This could mean isolating the guitar in a video of your band, filtering out traffic noises, or removing the sound of a dog barking in your podcast, all with text, visual, and time span prompts.

Meta Newsroom

204,678 views • 8 months ago

This is a big day. Meta is open-sourcing AudioCraft. You can now generate incredible music and sounds with a single prompt. It includes the most performant Generative AI Model (audio) on the market, the "Llama" of Audio. The research framework contains the weights and code of these models: ▸ MusicGen: controllable text-to-music model. ▸ AudioGen: text-to-sound model. ▸ EnCodec: high fidelity neural audio codec. ▸ Multi Band Diffusion: An EnCodec compatible decoder using diffusion. This is going to tremendously speed up audio research 👏

This is a big day. Meta is open-sourcing AudioCraft. You can now generate incredible music and sounds with a single prompt. It includes the most performant Generative AI Model (audio) on the market, the "Llama" of Audio. The research framework contains the weights and code of these models: ▸ MusicGen: controllable text-to-music model. ▸ AudioGen: text-to-sound model. ▸ EnCodec: high fidelity neural audio codec. ▸ Multi Band Diffusion: An EnCodec compatible decoder using diffusion. This is going to tremendously speed up audio research 👏

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CyberSudo

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Meet SAM 3, a unified model that enables detection, segmentation, and tracking of objects across images and videos. SAM 3 introduces some of our most highly requested features like text and exemplar prompts to segment all objects of a target category. Learnings from SAM 3 will help power new features in Instagram Edits and Vibes, bringing advanced segmentation capabilities directly to creators. 🔗 Learn more:

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AI at Meta

191,460 views • 8 months ago

As detailed in the Meta Movie Gen technical report, today we’re open sourcing Movie Gen Bench: two new media generation benchmarks that we hope will help to enable the AI research community to progress work on more capable audio and video generation models. Movie Gen Video Bench is the largest and most comprehensive benchmark ever released for evaluating text-to-video generation. It includes a collection of 1,000+ prompts that cover concepts ranging from detailed human activity to animals, physics, unusual subjects and more — with broad coverage across different motion levels. Movie Gen Audio Bench is a first-of-its-kind benchmark aimed at evaluating video-to-audio and (text+video)-to-audio generation. It includes 527 generated videos and associated sound effects and music prompts covering a diverse set of ambient environments and sound effects. To enable fair and easy comparison to our models for future works, these new benchmarks include non cherry-picked generated videos and audio from Movie Gen. In releasing these new benchmarks we hope to promote fair & extensive evaluations in media generation research to enable greater progress in this field.

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AI at Meta

156,273 views • 1 year ago

🎥 Today we’re premiering Meta Movie Gen: the most advanced media foundation models to-date. Developed by AI research teams at Meta, Movie Gen delivers state-of-the-art results across a range of capabilities. We’re excited for the potential of this line of research to usher in entirely new possibilities for casual creators and creative professionals alike. More details and examples of what Movie Gen can do ➡️ 🛠️ Movie Gen models and capabilities Movie Gen Video: 30B parameter transformer model that can generate high-quality and high-definition images and videos from a single text prompt. Movie Gen Audio: A 13B parameter transformer model that can take a video input along with optional text prompts for controllability to generate high-fidelity audio synced to the video. It can generate ambient sound, instrumental background music and foley sound — delivering state-of-the-art results in audio quality, video-to-audio alignment and text-to-audio alignment. Precise video editing: Using a generated or existing video and accompanying text instructions as an input it can perform localized edits such as adding, removing or replacing elements — or global changes like background or style changes. Personalized videos: Using an image of a person and a text prompt, the model can generate a video with state-of-the-art results on character preservation and natural movement in video. We’re continuing to work closely with creative professionals from across the field to integrate their feedback as we work towards a potential release. We look forward to sharing more on this work and the creative possibilities it will enable in the future.

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Meet MoshiVis🎙️🖼️, the first open-source real-time speech model that can talk about images! It sees, understands, and talks about images — naturally, and out loud. Voice interaction with a compact model endowed with visual understanding opens up new applications, from audio description for the visual impaired to visual access to information. Try it out 👉 Blog post 👉

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1,089,591 views • 8 months ago

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96,354 views • 1 year ago

Today we’re launching Stable Audio 2.5: The first audio model built for enterprise-grade sound production 🔊 Audio influences brand engagement by 86%, but few enterprises are leveraging audio as an extension of their brand, making customized sound an untapped differentiator. Stable Audio 2.5 is purpose-built for this opportunity to create customizable, high-quality audio at scale, with capabilities that include: ▶️ Improved musical composition: Generate full songs with multi-part structure, meaning a clear intro, middle, and outro. ▶️ Audio inpainting: Input audio, select where the track should start, and the model uses the context to generate the rest of the track. ▶️ Customization: Our team can fine-tune Stable Audio 2.5 to help enterprises create the right sound for their brand. ▶️ Faster inference: The model can generate up to three-minute long tracks in under two seconds on a GPU, outputting in just eight steps (compared to ~50 in the previous model). You can learn more here 👉

Stability AI

67,618 views • 11 months ago

Along with text, images, video and code, Gemini is able to process raw audio signal end-to-end. 🔊 It can listen to and understand speech, making it not only useful for transcription but a model that has a much more nuanced perception of its environment. ↓

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Google DeepMind

140,179 views • 2 years ago

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Pika

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Today we're announcing the open-source release of HunyuanVideo-Foley, our new end-to-end Text-Video-to-Audio (TV2A) framework for generating high-fidelity audio.🚀 This tool empowers creators in video production, filmmaking, and game development to generate professional-grade audio that precisely aligns with visual dynamics and semantic context, addressing key challenges in V2A generation.🔊 Key Innovations: 🔹Exceptional Generalization: Trained on a massive 100k-hour multimodal dataset, the model generates contextually-aware soundscapes for a wide range of scenes, from natural landscapes to animated shorts. 🔹Balanced Multimodal Response: Our innovative multimodal diffusion transformer (MMDiT) architecture ensures the model balances video and text cues, generating rich, layered sound effects that capture every detail—from the main subject to subtle background elements. 🔹High-Fidelity Audio: Using a Representation Alignment (REPA) loss function and a powerful Audio VAE, we've improved generation stability and producing professional-grade audio, free of noise and inconsistencies. HunyuanVideo-Foley achieves SOTA on multiple benchmarks, surpassing all open-source models in audio quality, visual-semantic alignment, and temporal alignment. 👉Try it now: 🌐Project Page: 🔗Code: 📄Technical Report: 🤗Hugging Face:

Tencent Hy

122,706 views • 11 months ago

I stopped writing giant video prompts. Now I build the audio first with Seed Audio 1.0. Dialogue, pauses, emotion, sound cues, all in one generation. Then I feed that audio into Seedance and the video follows the rhythm on its own. Timing, pacing, even camera feeling, all coming from the sound. Audio first. Video second. This is a different way to make AI films.

I stopped writing giant video prompts. Now I build the audio first with Seed Audio 1.0. Dialogue, pauses, emotion, sound cues, all in one generation. Then I feed that audio into Seedance and the video follows the rhythm on its own. Timing, pacing, even camera feeling, all coming from the sound. Audio first. Video second. This is a different way to make AI films.

Anabiya

56,435 views • 1 month ago

Introducing 𝘾𝙡𝙞𝙥𝘼𝙣𝙮𝙩𝙝𝙞𝙣𝙜, the first-ever multimodal AI clipping that lets you clip any moment from any video using visual, audio, and sentiment cues. 🔥 Analyze everything in any video ClipAnything uses state-of-the-art video understanding that analyzes each frame through visual, audio, and sentiment cues, identifying objects, scenes, actions, sounds, emotions, texts, and more. ⭐️ Use natural language prompts to find any moments You can use natural language prompts to find any scene, action, character, event, emotional moment, viral topic, and more. 🌶️ Create viral clips from any video Extending beyond talking-head videos, ClipAnything can clip any type of video, such as vlogs, sports, TV shows, news, music & videos with little to no dialogue. To learn more about it, please go to ClipAnything webpage:

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OpusClip

74,286 views • 2 years ago

How to train a model that actually understands both audio and text like Voxtral from Mistral AI? Here is a quick video walkthrough of the paper.

How to train a model that actually understands both audio and text like Voxtral from Mistral AI? Here is a quick video walkthrough of the paper.

Sophia Yang, Ph.D.

49,801 views • 1 year ago

experiment with bytedance's new SEED audio model... it's tricky to get consistent audio out of seedance prompts, esp if you want a multiclip story so i took the original 1min lowrez mulit-clip video i made here and handed it to both cc & codex with a FAL key... (more below)

experiment with bytedance's new SEED audio model... it's tricky to get consistent audio out of seedance prompts, esp if you want a multiclip story so i took the original 1min lowrez mulit-clip video i made here and handed it to both cc & codex with a FAL key... (more below)

Gavin Purcell

10,694 views • 1 month ago

Introducing Stable Audio 2.0 – a new model capable of producing high-quality, full tracks with coherent musical structure up to three minutes long at 44.1 kHz stereo from a single prompt. Explore the model and start creating for free at: Read the blogpost here: (1/3)

Introducing Stable Audio 2.0 – a new model capable of producing high-quality, full tracks with coherent musical structure up to three minutes long at 44.1 kHz stereo from a single prompt. Explore the model and start creating for free at: Read the blogpost here: (1/3)

Stability AI

457,863 views • 2 years ago

Researchers at Meta recently shared MAGNeT, a single non-autoregressive transformer model for text-to-music & text-to-sound generation capable of generating audio on-par with the quality of SOTA models — at 7x the speed. MAGNeT is open source as part of AudioCraft. Hear audio samples and get more details on this work ➡️

Researchers at Meta recently shared MAGNeT, a single non-autoregressive transformer model for text-to-music & text-to-sound generation capable of generating audio on-par with the quality of SOTA models — at 7x the speed. MAGNeT is open source as part of AudioCraft. Hear audio samples and get more details on this work ➡️

AI at Meta

122,001 views • 2 years ago

🚀 Introducing Community Benchmarks on Kaggle! As AI evolves at an unprecedented pace, measuring intelligence requires more than a few AI research labs alone – it requires the imagination and collective expertise of the global community. That’s why we’re launching Community Benchmarks. It lets you build, run, and share custom AI benchmarks that are evaluated on the leading AI models with transparent, reproducible results. Learn more:

🚀 Introducing Community Benchmarks on Kaggle! As AI evolves at an unprecedented pace, measuring intelligence requires more than a few AI research labs alone – it requires the imagination and collective expertise of the global community. That’s why we’re launching Community Benchmarks. It lets you build, run, and share custom AI benchmarks that are evaluated on the leading AI models with transparent, reproducible results. Learn more:

Kaggle

54,577 views • 7 months ago