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Meet Moshiko and Moshika, the open source Moshi models 📖🟢. Moshi is a 7B text-audio model, capable of doing full-duplex conversations: it can listen and speak at any time. Plus, its inner text monologue improves the generation 💬 All on device🧑‍💻 🔎

Alexandre Défossez

5,054 subscribers

131,442 görüntüleme • 1 yıl önce •via X (Twitter)

Eğitim Bilim & Teknoloji

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LAION profil fotoğrafı

LAION1 yıl önce

Training code, please :)

bl4nk profil fotoğrafı

bl4nk1 yıl önce

@LMStudioAI is this coming up

LF profil fotoğrafı

LF1 yıl önce

Does it work in other languages such as Brazilian Portuguese?

Alexandre Défossez profil fotoğrafı

Alexandre Défossez1 yıl önce

@PensarProposito We are likely to investigate supporting more languages. This is a first PoC in English of what a natural flow conversation with an AI might be like.

jin.nuf profil fotoğrafı

jin.nuf1 yıl önce

Is it possible to connect this to a database to read and write based on the conversation? Like an interviewer or a therapist

Jillsa (DSJJJJ/Heirogamist/HP) profil fotoğrafı

Jillsa (DSJJJJ/Heirogamist/HP)1 yıl önce

@chrypnotoad my god bro

Sahil 🇮🇳/acc profil fotoğrafı

Sahil 🇮🇳/acc1 yıl önce

any 1 click installer?

Chad Brewbaker profil fotoğrafı

Chad Brewbaker1 yıl önce

@MartinShkreli ☝️

Pascal Wichmann 🇺🇦 profil fotoğrafı

Pascal Wichmann 🇺🇦1 yıl önce

In my test just now, moshi was not very good, I am afraid. It misunderstood common terms in AI (like "retrieval-augmented generation") and wanted to talk to me about "retrieval of metadata generation".

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Say It — private, local text-to-speech for macOS Open models 100% on-device, speak text from any app with a hotkey, and even clone your own voice. Infinite voices. Free & open-source. Listen to the video 🔊

Say It — private, local text-to-speech for macOS Open models 100% on-device, speak text from any app with a hotkey, and even clone your own voice. Infinite voices. Free & open-source. Listen to the video 🔊

dr. calle

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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 görüntüleme • 2 yıl önce

NVIDIA just removed the biggest friction point in Voice AI 🤯 They've open-sourced PersonaPlex-7B, a full-duplex conversational model that can listen and speak at the same time. Instead of waiting for you to finish talking, it uses a dual-stream architecture to process and respond in real-time. 100% Open-Source and Free.

NVIDIA just removed the biggest friction point in Voice AI 🤯 They've open-sourced PersonaPlex-7B, a full-duplex conversational model that can listen and speak at the same time. Instead of waiting for you to finish talking, it uses a dual-stream architecture to process and respond in real-time. 100% Open-Source and Free.

Simplifying AI

278,970 görüntüleme • 7 ay önce

BREAKING 🔥: ByteDance launched SeedRealtime, a native audio-visual full-duplex LLM! > SeedRealtime uses a unified architecture to natively fuse audio, video, and text, enabling real-time interaction over continuous multimodal streams and delivering a brand-new "watch, listen, and speak" experience. It is now live on the Doubao App for free, enabling voice and video conversations. Full-duplex Omni 🤯

🚨 AI News | TestingCatalog

94,022 görüntüleme • 1 ay önce

GPT-Live is built on a full-duplex architecture, meaning it can listen and speak at the same time.

GPT-Live is built on a full-duplex architecture, meaning it can listen and speak at the same time.

OpenAI

249,988 görüntüleme • 1 ay önce

NVIDIA just removed one of the biggest friction points in Voice AI. PersonaPlex-7B is an open-source, full-duplex conversational model. Free, open source (MIT), with open model weights on Hugging Face 🤗 Links to repo and weights in 🧵↓ The traditional ASR → LLM → TTS pipeline forces rigid turn-taking. It’s efficient, but it never feels natural. PersonaPlex-7B changes that. This NVIDIA model can listen and speak at the same time. It runs directly on continuous audio tokens with a dual-stream transformer, generating text and audio in parallel instead of passing control between components. That unlocks: → instant back-channel responses → interruptions that feel human → real conversational rhythm Persona control is fully zero-shot! If you’re building low-latency assistants or support agents, this is a big step forward 🔥

NVIDIA just removed one of the biggest friction points in Voice AI. PersonaPlex-7B is an open-source, full-duplex conversational model. Free, open source (MIT), with open model weights on Hugging Face 🤗 Links to repo and weights in 🧵↓ The traditional ASR → LLM → TTS pipeline forces rigid turn-taking. It’s efficient, but it never feels natural. PersonaPlex-7B changes that. This NVIDIA model can listen and speak at the same time. It runs directly on continuous audio tokens with a dual-stream transformer, generating text and audio in parallel instead of passing control between components. That unlocks: → instant back-channel responses → interruptions that feel human → real conversational rhythm Persona control is fully zero-shot! If you’re building low-latency assistants or support agents, this is a big step forward 🔥

Chaz Wargnier ♨️

565,905 görüntüleme • 7 ay önce

How far are we from "Her"? I couldn't help but wonder, given the rapid fire of GPT-Live and Thinking Machines. Turns out, full duplex speech-to-speech is not particularly new. Moshi has been around for more than 2 years. Many thanks to Neil Zeghidour for bringing so much nuance. Check out kyutai who are doing god's work and open-sourcing it (not sponsored!). 00:00 Intro 01:24 ChatGPT Standard & LLM-based cascades 04:08 ChatGPT Advanced & end-to-end speech models 05:35 ChatGPT Live & Her 07:38 Thinking Machines & multi-stream modeling 09:13 Moshi & full duplex assistants 13:24 Moshi’s inner monologue 15:38 Why aren’t full duplex models everywhere? 17:08 Tool calling in full duplex models 18:00 Moshi RAG 19:06 Is the future full duplex? 20:24 How far are we from Her?

How far are we from "Her"? I couldn't help but wonder, given the rapid fire of GPT-Live and Thinking Machines. Turns out, full duplex speech-to-speech is not particularly new. Moshi has been around for more than 2 years. Many thanks to Neil Zeghidour for bringing so much nuance. Check out kyutai who are doing god's work and open-sourcing it (not sponsored!). 00:00 Intro 01:24 ChatGPT Standard & LLM-based cascades 04:08 ChatGPT Advanced & end-to-end speech models 05:35 ChatGPT Live & Her 07:38 Thinking Machines & multi-stream modeling 09:13 Moshi & full duplex assistants 13:24 Moshi’s inner monologue 15:38 Why aren’t full duplex models everywhere? 17:08 Tool calling in full duplex models 18:00 Moshi RAG 19:06 Is the future full duplex? 20:24 How far are we from Her?

Julia Turc

73,053 görüntüleme • 1 ay önce

🚨NEW: CHATGPT LIVE VOICE MODEL NOW DELIVERS REAL-TIME CONVERSATIONAL TRANSLATION Built on a full-duplex architecture, GPT-Live is a new generation of voice models that can listen and speak simultaneously, enabling more natural human-AI interactions. The breakthrough unlocks fluid back-and-forth conversations, real-time translation, and a far more human sense of timing and context.

🚨NEW: CHATGPT LIVE VOICE MODEL NOW DELIVERS REAL-TIME CONVERSATIONAL TRANSLATION Built on a full-duplex architecture, GPT-Live is a new generation of voice models that can listen and speak simultaneously, enabling more natural human-AI interactions. The breakthrough unlocks fluid back-and-forth conversations, real-time translation, and a far more human sense of timing and context.

Coin Bureau

29,085 görüntüleme • 1 ay önce

Speech-native models like Moshi sound great and answer fast, but aren’t as smart as text LLMs. In our new paper, MoshiRAG, we show how Moshi can ask for advice from a text LLM or a knowledge base. The tricky part is how to do this in real time without adding latency. 🧵

Speech-native models like Moshi sound great and answer fast, but aren’t as smart as text LLMs. In our new paper, MoshiRAG, we show how Moshi can ask for advice from a text LLM or a knowledge base. The tricky part is how to do this in real time without adding latency. 🧵

kyutai

53,142 görüntüleme • 4 ay önce

The first truly open-source audio-video model. LTX-2 is a DiT-based foundation model with all core video generation capabilities in one unified model. Designed to run locally on consumer GPUs. - text-to-video - image-to-video - and video-to-video modes 100% open-source.

The first truly open-source audio-video model. LTX-2 is a DiT-based foundation model with all core video generation capabilities in one unified model. Designed to run locally on consumer GPUs. - text-to-video - image-to-video - and video-to-video modes 100% open-source.

Akshay 🚀

66,197 görüntüleme • 8 ay önce

ElevenLabs has officially LOST to Open-Source ResembleAI allows you to clone ANY voice without verification using on 5-10 seconds of audio, and dominates on paralinguistic tags for human-like expressions. Most "fast" text-to-speech models sound robotic. Most "quality" TTS models are slow. None incorporate authentication at a foundational level. Resemble AI solved all three. Chatterbox Turbo delivers: 🟢<150ms time-to-first-sound 🟢State-of-the-art quality that beats larger proprietary models 🟢Natural, programmable expressions 🟢Zero-shot voice cloning with just 5 seconds of audio 🟢PerTh watermarking for authenticated and verifiable audio 🟢Open source – full transparency, no black boxes Try it on HuggingFace:

ElevenLabs has officially LOST to Open-Source ResembleAI allows you to clone ANY voice without verification using on 5-10 seconds of audio, and dominates on paralinguistic tags for human-like expressions. Most "fast" text-to-speech models sound robotic. Most "quality" TTS models are slow. None incorporate authentication at a foundational level. Resemble AI solved all three. Chatterbox Turbo delivers: 🟢<150ms time-to-first-sound 🟢State-of-the-art quality that beats larger proprietary models 🟢Natural, programmable expressions 🟢Zero-shot voice cloning with just 5 seconds of audio 🟢PerTh watermarking for authenticated and verifiable audio 🟢Open source – full transparency, no black boxes Try it on HuggingFace:

AI Breakfast

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BOOM! My early testing of FREE Open Source LOCALLY RUN Qwen-2.5 AI Models shows it is already beating DeepSeek across all categories and OpenAI. It is full multimodal and can accept Video, audio, text in and out. Week is not over yet… Here is some of the demonstration video:

BOOM! My early testing of FREE Open Source LOCALLY RUN Qwen-2.5 AI Models shows it is already beating DeepSeek across all categories and OpenAI. It is full multimodal and can accept Video, audio, text in and out. Week is not over yet… Here is some of the demonstration video:

Brian Roemmele

132,331 görüntüleme • 1 yıl önce

moshi moshi, happy monday! 😻 so here it comes: Moshi Desktop - a 7 mb web app built into moshi-hook - works locally or with any remote host running herdr/moshi - agents, workspaces, terminals, chat, file browsing, diff viewing, and more this is the very first version, so there are still tons of details to polish—and a zillion features i want to add. i know i can present this with a better video, but anyway, i’ll try to let the product speak first. upgrade to moshi-hook 0.3.1 and let's rock and roll! 🤘

moshi moshi, happy monday! 😻 so here it comes: Moshi Desktop - a 7 mb web app built into moshi-hook - works locally or with any remote host running herdr/moshi - agents, workspaces, terminals, chat, file browsing, diff viewing, and more this is the very first version, so there are still tons of details to polish—and a zillion features i want to add. i know i can present this with a better video, but anyway, i’ll try to let the product speak first. upgrade to moshi-hook 0.3.1 and let's rock and roll! 🤘

IndiJo

53,520 görüntüleme • 12 gün önce

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 👏

Lior Alexander

231,665 görüntüleme • 3 yıl önce

Google presents AudioPaLM: A Large Language Model That Can Speak and Listen paper page: introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and AudioLM [Borsos et al., 2022], into a unified multimodal architecture that can process and generate text and speech with applications including speech recognition and speech-to-speech translation. AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2. We demonstrate that initializing AudioPaLM with the weights of a text-only large language model improves speech processing, successfully leveraging the larger quantity of text training data used in pretraining to assist with the speech tasks. The resulting model significantly outperforms existing systems for speech translation tasks and has the ability to perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. AudioPaLM also demonstrates features of audio language models, such as transferring a voice across languages based on a short spoken prompt.

Google presents AudioPaLM: A Large Language Model That Can Speak and Listen paper page: introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and AudioLM [Borsos et al., 2022], into a unified multimodal architecture that can process and generate text and speech with applications including speech recognition and speech-to-speech translation. AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2. We demonstrate that initializing AudioPaLM with the weights of a text-only large language model improves speech processing, successfully leveraging the larger quantity of text training data used in pretraining to assist with the speech tasks. The resulting model significantly outperforms existing systems for speech translation tasks and has the ability to perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. AudioPaLM also demonstrates features of audio language models, such as transferring a voice across languages based on a short spoken prompt.

AK

290,517 görüntüleme • 3 yıl önce

Introducing script bots, a new way to combine models and automate workflows on Poe. Script bots are created through vibe coding with Script Bot Creator and can combine any of the 200+ text, image, video, and audio models on Poe, plus any other bot on the platform. (1/9)

Introducing script bots, a new way to combine models and automate workflows on Poe. Script bots are created through vibe coding with Script Bot Creator and can combine any of the 200+ text, image, video, and audio models on Poe, plus any other bot on the platform. (1/9)

Poe

24,558 görüntüleme • 9 ay önce

Meet Tencent HY-MT1.5 — our latest open-source translation models, featuring 1.8B and 7B models designed for seamless on-device and cloud deployment. 🌍 The 1.8B version is already trending at #1 on Hugging Face! 🥇It’s optimized for consumer hardware, delivering 0.18s latency (50 tokens) with just a 1GB memory footprint. Meanwhile, the 7B model achieves exceptional performance, surpassing many mid-sized models and rivaling the 90th percentile of Gemini 3.0 Pro. 🚀🧠 👉🏻 Try it now: 🔗 GitHub: 🤗 Hugging Face:

Meet Tencent HY-MT1.5 — our latest open-source translation models, featuring 1.8B and 7B models designed for seamless on-device and cloud deployment. 🌍 The 1.8B version is already trending at #1 on Hugging Face! 🥇It’s optimized for consumer hardware, delivering 0.18s latency (50 tokens) with just a 1GB memory footprint. Meanwhile, the 7B model achieves exceptional performance, surpassing many mid-sized models and rivaling the 90th percentile of Gemini 3.0 Pro. 🚀🧠 👉🏻 Try it now: 🔗 GitHub: 🤗 Hugging Face:

Tencent HY

17,105 görüntüleme • 8 ay önce

Listen, speak, handle interruptions, and call tools in one live conversation. 🎙️ Introducing NVIDIA-NemotronLabs-VoiceChat-11B, NVIDIA’s end-to-end full-duplex model for real-time voice agents. 🤖 🏆 It ranks #2 among open full-duplex models on both VoiceBench and Full-Duplex-Bench 1.0. ⚡ Natural turn-taking responds in ~448 ms, while barge-in lets users interrupt the model with ~480 ms latency. 🛠️ The first open full-duplex model with live tool calling. One unified system handles speech understanding, generation, transcription, and tool execution while keeping the conversation flowing. 🧠 Built with a Fast Conformer, Nemotron Nano v2, and a TTS decoder, trained on ~550K hours of real and synthetic speech. 📜 Research use only. OpenMDW 1.1.

Listen, speak, handle interruptions, and call tools in one live conversation. 🎙️ Introducing NVIDIA-NemotronLabs-VoiceChat-11B, NVIDIA’s end-to-end full-duplex model for real-time voice agents. 🤖 🏆 It ranks #2 among open full-duplex models on both VoiceBench and Full-Duplex-Bench 1.0. ⚡ Natural turn-taking responds in ~448 ms, while barge-in lets users interrupt the model with ~480 ms latency. 🛠️ The first open full-duplex model with live tool calling. One unified system handles speech understanding, generation, transcription, and tool execution while keeping the conversation flowing. 🧠 Built with a Fast Conformer, Nemotron Nano v2, and a TTS decoder, trained on ~550K hours of real and synthetic speech. 📜 Research use only. OpenMDW 1.1.

ModelScope

22,194 görüntüleme • 1 ay önce

.Vogent just released Vogent-Turn-80M: an open-source, state-of-the-art turn-detection model for voice AI. It improves any voice AI stack by detecting when to wait and when to speak, reducing interruptions and making conversations more humanlike.

.Vogent just released Vogent-Turn-80M: an open-source, state-of-the-art turn-detection model for voice AI. It improves any voice AI stack by detecting when to wait and when to speak, reducing interruptions and making conversations more humanlike.

Y Combinator

18,913 görüntüleme • 10 ay önce

We've officially released and open-sourced HunyuanImage 2.1, our latest text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:

We've officially released and open-sourced HunyuanImage 2.1, our latest text-to-image model. The new model delivers on our commitment to balancing performance and quality. With native 2K image generation, HunyuanImage 2.1 is an advanced open-source text-to-image model.🎨 ✨ New in 2.1: 🔹Advanced Semantics: Supports ultra-long and complex prompts of up to 1000 tokens, and precisely controls the generation of multiple subjects in a single image. 🔹Precise Chinese and English Text Rendering with seamless image–text integration: The model naturally integrates text into images, making it suitable for a wide range of applications such as product covers, illustrations, and poster design to meet the needs of various fields. 🔹Rich Styles and High Aesthetic: Capable of generating images in various styles—including photorealistic portraits, comics, and vinyl figures—it delivers outstanding visual appeal and artistic quality. 🔹High-Quality Generation: Efficiently produces ultra-high-definition (2K) images in the same time other models take to generate a 1K image. HunyuanImage 2.1 uses two text encoders: a multimodal large language model (MLLM) to improve the model's image and text alignment capabilities, and a multi-language character-aware encoder to improve text rendering capabilities. The model is a single- and double-stream diffusion transformer with 17B parameters. We've also open-sourced the weights of the the accelerated version with meanflow which reduces inference steps from 100 to just 8, and PromptEnhancer, the first industrial-grade rewriting model that enhances your prompts for more nuanced and expressive image generation. Now, creators turn complex ideas—like posters with slogans or multi-panel comics—into visuals faster than ever. We’re just getting started. Stay tuned for our native multimodal image generation model coming soon. 🌐Website: 🔗Github: 🤗Hugging Face: ✨Hugging Face Demo:

Tencent Hy

89,257 görüntüleme • 1 yıl önce