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Eleven v3 (alpha) is the most expressive Text to Speech model. v3 introduces: • Multi-speaker dialogue with contextual awareness • Support for 70+ languages, up from 33 in v2 • Audio tags such as [excited], [sighs], [laughing], and [whispers]

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ElevenLabs

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39,346 просмотров • 1 год назад •via X (Twitter)

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Фото профиля ElevenLabs
ElevenLabs1 год назад

Learn how to get the most out of Eleven v3 with our v3 Prompting Tutorial: • Use longer prompts – v3 performs better with longer inputs • Pick the right voice from our v3 Collection • Use [audio tags] to control delivery • Keep experimenting

Фото профиля ElevenLabs
ElevenLabs1 год назад

Create shareable v3 videos with our new “Share to Video” feature. To share your best creations: • Click the share icon in the Text to Speech editor • Select "Generate video" • Choose a color scheme • Download and post your video

Фото профиля ElevenLabs
ElevenLabs1 год назад

We want to hear your best v3 voice generations, so we’re rewarding the most creative voice prompters with prizes. Enter our Eleven v3 competition below.

Фото профиля ElevenLabs
ElevenLabs1 год назад

Get started with Eleven v3, the most expressive Text to Speech model, at

Фото профиля Alex ZAP
Alex ZAP1 год назад

🚀 Revolutionize your QA testing with ZAPTEST AI! ZAPTEST automates testing, slashes costs & boosts ROI up to 10X. No coding needed—just faster, smarter automation. 📅 Book your live demo now:

Фото профиля James McAulay ❙❙ ElevenLabs
James McAulay ❙❙ ElevenLabs1 год назад

Incredible work on this 🔥 launch video from @_krocits_ @JavierRend71980 and the inimitable Jack Maltby 👏

Фото профиля GraphAI
GraphAI1 год назад

This is satisfying 👌

Фото профиля ص
ص1 год назад

Bring it to dubbing PLEASE!

Фото профиля Zaid
Zaid1 год назад

api wen?

Фото профиля HaronBkc
HaronBkc1 год назад

¿?

Фото профиля Felipe H 🦾
Felipe H 🦾1 год назад

Is it API available for everyone?

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Introducing Eleven v3 (alpha) - the most expressive Text to Speech model ever. Supporting 70+ languages, multi-speaker dialogue, and audio tags such as [excited], [sighs], [laughing], and [whispers]. Now in public alpha and 80% off in June.
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Introducing Eleven v3 (alpha) - the most expressive Text to Speech model ever. Supporting 70+ languages, multi-speaker dialogue, and audio tags such as [excited], [sighs], [laughing], and [whispers]. Now in public alpha and 80% off in June.

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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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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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Here are the best practices for using Eleven v3 (alpha) - the most expressive Text to Speech model.
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Here are the best practices for using Eleven v3 (alpha) - the most expressive Text to Speech model.

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ElevenLabs v3 is now on Poe! With new audio tags, multi-speaker support, and options for over 70 languages, this category leading model gives you more control to create audio that feels more real, natural and expressive. (1/2)
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Eleven v3 now supports Text to Speech in 41 new languages - bringing the total to over 70. This means you can now reach over 90% of the global population with ElevenLabs.
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Eleven v3 now supports Text to Speech in 41 new languages - bringing the total to over 70. This means you can now reach over 90% of the global population with ElevenLabs.

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Voice Design v3 is here. Create any voice you can imagine with a prompt. We’ve rebuilt the underlying Voice Design model to deliver higher quality and broader expressive range. Generate production-ready voices in 70+ languages with support for hundreds of localized accents.
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Today we launched Eleven v3 to alpha. It's our most expressive and dynamic speech model to date. Check out the landing page which showcases some of the incredible, creative outputs that the model is capable of.
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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.
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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.

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