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Introducing Parrot 🦜 Our first speech-to-text model built for production-grade voice agents with an industry leading accuracy, built for noisy calls, regional dialects and compressed audio. Trained on thousands of hours of real-world audio to make sure when you say Udaipur, the agent doesn't hear 'you-die-poor'.

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Vedant

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15,641 görüntüleme • 1 ay önce •via X (Twitter)

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Universal-Streaming is our real-time speech-to-text model — built for voice agents with ~300ms latency, high accuracy, unlimited concurrency, and just $0.15/hour. 👉 Test it live in the playground →
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Universal-Streaming is our real-time speech-to-text model — built for voice agents with ~300ms latency, high accuracy, unlimited concurrency, and just $0.15/hour. 👉 Test it live in the playground →

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Wow! New Speech to Speech model - Fish Agent v0.1 3B by Fish Audio 🔥 > Trained on 700K hours of multilingual audio > Continue-pretrained version of Qwen-2.5-3B-Instruct for 200B audio & text tokens > Zero-shot voice cloning > Text + audio input/ Audio output > Ultra-fast inference w/ 200ms TTFA > Models on the Hub & Finetuning code on its way! 🚀 What an amazing time to be alive 🤗

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Maven Voice is our enterprise-grade AI voice agent built for the chaotic, noisy and unpredictable situations we encounter everyday. Thank you to OpenAI, Phonic, , and for helping make this possible.
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Maven Voice is our enterprise-grade AI voice agent built for the chaotic, noisy and unpredictable situations we encounter everyday. Thank you to OpenAI, Phonic, , and for helping make this possible.

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Day 1 of 3 days of MLX: Introducing MLX-Audio-Swift SDK 🚀 A modular Swift SDK for voice agents and tasks on Apple Silicon built by Lucas Newman and yours truly. iOS, macOS, and visionOS developers can now build native apps with real-time, on-device audio intelligence: 🗣️ Text-to-Speech (TTS) 👂 Speech-to-Text (STT) 🔄 Speech-to-Speech (STS) 🎙️ Voice Activity Detection (VAD) and more. Only import the capabilities you need, nothing extra. Get started today and leave us a star ⭐️
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Day 1 of 3 days of MLX: Introducing MLX-Audio-Swift SDK 🚀 A modular Swift SDK for voice agents and tasks on Apple Silicon built by Lucas Newman and yours truly. iOS, macOS, and visionOS developers can now build native apps with real-time, on-device audio intelligence: 🗣️ Text-to-Speech (TTS) 👂 Speech-to-Text (STT) 🔄 Speech-to-Speech (STS) 🎙️ Voice Activity Detection (VAD) and more. Only import the capabilities you need, nothing extra. Get started today and leave us a star ⭐️

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NEW: Kokoro 82M - APACHE 2.0 licensed, Text to Speech model, trained on < 100 hours of audio 🔥
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NEW: Kokoro 82M - APACHE 2.0 licensed, Text to Speech model, trained on < 100 hours of audio 🔥

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This is the best and fastest speech-to-text model in the world: • 23.2 seconds to process 30 minutes of audio • 93.3% accuracy • Diarization support to detect multiple speakers • Trained on 12.5 million hours of multilingual data I tried it out and it's pretty impressive:

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Introducing Tongyi Fun – Alibaba’s enterprise-grade audio foundation model. Powered by Fun-ASR and Fun-CosyVoice it advances voice AI beyond “hearing and speaking” to truly understand context, transcribe with high accuracy, and speak with natural expressiveness—even in complex enterprise environments. ✅ Understands deeply: Trained on tens of millions of hours of real-world audio, with industry-specific terminology across finance, tech, manufacturing, and more. ✅ Transcribes accurately: A context-enhanced architecture with RAG minimizes errors, hallucinations, and cross-language interference. ✅ Speaks expressively: Delivers natural, stable, multilingual speech synthesis with cross-lingual voice cloning.

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Your customer support needs a voice agent built for the real world. Grok Voice Think Fast 1.0 handles complex workflows with speed and accuracy, even in hard-to-hear environments. From multi-step troubleshooting to high-volume tool calls, it keeps up.

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🔊Introducing Voxtral TTS: our new frontier open-weight model for natural, expressive, and ultra-fast text-to-speech 🎭Realistic, emotionally expressive speech. 🌍Supports 9 languages and accurately captures diverse dialects. ⚡Very low latency for time-to-first-audio. 🔄Easily adaptable to new voices

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Some examples: - Text to Speech: Read aloud content or create audiobooks. - Speech to Text: Transcribe audio and video into text. - Voice Designer: Create custom AI voices. - Conversational AI: Build dynamic voice agents and make outbound calls.

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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 👉

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We are launching the Eleven v3 (alpha) API. Built for async use cases, Eleven v3 (alpha) delivers the most expressive Text to Speech model: - Dialogue mode, unlimited amount of speakers - 70+ languages - Enhanced voice and emotional control with [audio tags]

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Introducing Atlas 1. Willow's new frontier speech-to-text model. It outperforms ElevenLabs, Deepgram, OpenAI, and more by a wide margin. Built on the first scalable, human-powered transcription infrastructure ever built for real-time dictation.

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Introducing the official ElevenLabs MCP server. Give Claude and Cursor access to the entire ElevenLabs AI audio platform via simple text prompts. You can even spin up voice agents to perform outbound calls for you — like ordering pizza.

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Introducing Qwen3-TTS! 🗣️ Our new text-to-speech model is designed to be multi-timbre, multi-lingual, and multi-dialect for natural, expressive audio. It delivers strong performance in English & Chinese, and we're excited for you to hear it for yourself!

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I built a simple voice assistant in 70 lines of Python code. It uses: • LiveKit - The voice agent • AssemblyAI - To turn your voice into text • OpenAI - The brain of the agent, and to turn text into audio There's something really cool about this:

Santiago

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Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.
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Introducing Lightning V3 - it beats every model we tested against. ElevenLabs, Cartesia, OpenAI. Lightning sets a new SOTA with V3 in conversational text-to-speech. → Highest MOS score for conversational TTS at 3.9 → ~76% win rate vs gpt-4o-mini-tts on naturalness → 15 languages with mid-sentence code-switching → Built from scratch for voice agents, not read-aloud Every TTS model sounds clean in a demo. You type a sentence and you get beautiful audio. Voice agents don't work that way. They stream. They're generating audio in real-time chunks with half the context missing. That's where everything breaks. A great reading voice and a great conversational voice are fundamentally different things. A conversational voice has to sound like it's thinking - with the pauses, the rhythm shifts, the reactions. It has to handle the way real people actually talk, including switching languages mid-sentence. That's what V3 does. V3.1 also ships voice cloning. 5 to 15 seconds of audio, no fine-tuning, production-grade clone across 15 languages. Blog link in the comments.

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Introducing Wan 2.5 🚀 Create immersive AI videos with fluid motion, built-in audio and voice. Supporting text-to-video and start images Available now for all users
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Introducing Wan 2.5 🚀 Create immersive AI videos with fluid motion, built-in audio and voice. Supporting text-to-video and start images Available now for all users

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We’re finally breaking the silence 🔊 Meet Higgsfield Audio, our all-in-one AI audio generator. Higgsfield is now the ultimate full-cycle AI content production platform. 🧩 Give a voice to any of your text with 21 voice presets 🧩 Change the voice in any of your videos 🧩 Translate and lip-sync any speech in 10 built-in languages An end-to-end AI workflow under one subscription.

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