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Only Models#Voice
  1. ElevenLabs Blog65

    Introducing Scribe v3 and v3 Live, our most accurate speech to text models

    ElevenLabs launched Scribe v3 for recorded audio, which makes 27% fewer word errors than Scribe v2 across 102 languages and has the lowest diarization error of any model tested, and Scribe v3 Live for realtime audio, which makes 43% fewer semantic word errors than Scribe v2 Realtime and adds speaker diarization and improved turn detection. Scribe v3 Live is available today in ElevenAgents, and both models are available in ElevenAPI, where switching from Scribe v2 is a one-line change to the model ID (scribe_v3 or scribe_v3_live). Both run in the US by default with isolated EU, India, and Singapore environments, Zero Retention Mode, and SOC 2, ISO 27001, PCI DSS Level 1, and HIPAA-eligible coverage.

    Why it matters: Useful for teams choosing speech-to-text models, since it details measured accuracy, diarization, and latency trade-offs plus deployment and compliance options.

  1. Hugging Face Blog71

    A Closer Look at Phonon TTS. Launching High-Quality On-Device Speech That Tops the Benchmarks.

    Gradium details Phonon, a small on-device text-to-speech model released two weeks ago that needs no server or network, with Phonon 31m (English) under Apache 2.0 and Phonon 40m covering English, French, German, Spanish and Portuguese under a non-commercial license. The models, about 65 MB and 75 MB, offer over 100 built-in voices plus voice cloning and voice design, and on Hugging Face's Open TTS Leaderboard Phonon ranks first in German and Spanish on intelligibility and tops the CPU streaming benchmark on time-to-first audio. The post also covers the ptts inference framework, Transformers integration from v5.21, launch demos, and more than 200,000 downloads in the first two weeks.

    Why it matters: It offers a detailed look at how a small on-device TTS model was built, benchmarked and integrated into developer tooling.

  1. Hugging Face Blog78

    NVIDIA Nemotron 3.5 Transcribe and Granary v2: Intelligent Multilingual Transcription You Can Prompt and Adapt

    NVIDIA released Nemotron 3.5 Transcribe, an open-weight, promptable model that handles transcription in 40 languages, translation of 31 to or from English, speaker attribution in 13 languages, and audio question answering in one checkpoint, running on a single NVIDIA GPU. It ranks first among open-weight models on the Hugging Face Open ASR Leaderboard for English at 5.33% average WER and posts the lowest diarization error rate on David AI's 21-language leaderboard. The release also includes Granary v2, an open data curation pipeline covering 463,062 hours across 48 languages, and NeMo Speech fine-tuning recipes that cut held-out WER by 45.8% relative to the best prompt in a medical case study.

    Why it matters: It documents concrete benchmark standings, an open data pipeline, and a reproducible fine-tuning recipe for teams evaluating or adapting open speech models.

  1. Mistral AI80

    Voxtral 3

    Mistral introduces Voxtral 3, a family of speech-to-text and text-to-speech models plus a LiveKit-based voice agent SDK that combines listening, reasoning, tool calling and speaking in one real-time streaming pipeline. It includes Voxtral Small Transcribe 3 for multilingual transcription with diarization and context biasing, Voxtral Mini TTS 3 for expressive speech in 35+ languages and 50+ dialects, and Pro Voice adaptation from 30 minutes of audio. It is available via Mistral's EU-hosted API or self-deployment, with pricing from $0.0035/min for batch transcription to $13 per 1M characters for TTS.

    Why it matters: The announcement details concrete model capabilities, benchmarks and pricing for teams evaluating real-time voice agents and sovereign speech deployment.

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