NVIDIA Parakeet
NVIDIA Parakeet-RNNT-1.1B is a multilingual automatic speech recognition model built for quality transcription across voice applications. With 1.1 billion parameters and training on more than 90,000 hours of speech, it supports 25 languages and regional variants, including English, Spanish, French, German, Italian, Arabic, Japanese, Korean, Portuguese, Russian, Hindi, Dutch, Danish, Norwegian, Czech, Polish, Swedish, Thai, Turkish, and Hebrew. The model automatically detects the spoken language and uses a universal tokenizer created by training language-specific tokenizers and merging them into a shared vocabulary, enabling efficient cross-lingual learning and deployment. Parakeet-RNNT produces case-sensitive transcripts with upper and lowercase text, punctuation, spaces, and apostrophes, making the output suitable for production voice applications and downstream language understanding.
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MAI-Voice-2
MAI-Voice-2 is Microsoft AI’s most expressive and natural-sounding text-to-speech model to date, built for production voice experiences where fidelity, language coverage, speaker consistency, and emotional range directly shape the user experience. It is designed for assistants, customer support, audiobooks, accessibility experiences, games, podcasts, courses, simulations, and creator workflows where voice quality must sound natural, fluid, and trustworthy. It expands from English-only support to 15 languages while maintaining naturalness and expressiveness, with support for English, Italian, French, German, Hindi, Spanish, Portuguese, Korean, Chinese, Turkish, Russian, Thai, Dutch, Romanian, and Hungarian. MAI-Voice-2 offers granular emotion control through tags such as sad, whispered, and excited, along with role-based expressive speech for experiences like motivational trainers, sports commentators, or character voices.
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Mintza
Mintza teaches you to speak a new language by actually speaking it, in live voice conversations with a bilingual AI teacher. Pick the language you speak and the one you are learning, then talk: real-time voice with natural pacing, no transcripts and no waiting for the app to think. When you freeze or slip up, your teacher corrects you in the moment, and if you get stuck it helps you in the language you already know, then brings you back.
Fifteen languages in any pairing and direction: English, Spanish, Portuguese, French, Italian, German, Greek, Chinese, Russian, Turkish, Swedish, Arabic, Japanese, Korean, and Hebrew, with regional accents such as Argentine Spanish, Parisian French, or Brazilian Portuguese. Rehearse a job interview, order coffee, navigate a doctor visit, or just chat about your day.
Sign in with Apple or Google for 10 free minutes, then subscribe for monthly conversation minutes. Available on iPhone, iPad, and Android.
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Qwen3-TTS
Qwen3-TTS is an open source series of advanced text-to-speech models developed by the Qwen team at Alibaba Cloud under the Apache-2.0 license, offering stable, expressive, and real-time speech generation with features such as voice cloning, voice design, and fine-grained control of prosody and acoustic attributes. The models support 10 major languages, including Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian, and multiple dialectal voice profiles with adaptive control over tone, speaking rate, and emotional expression based on text semantics and instructions. Qwen3-TTS uses efficient tokenization and a dual-track architecture that enables ultra-low-latency streaming synthesis (first audio packet in ~97 ms), making it suitable for interactive and real-time use cases, and includes a range of models with different capabilities (e.g., rapid 3-second voice cloning, custom voice timbres, and instruction-based voice design).
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