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Voice>Text — AI Voice Cloning in 100+ Languages
Bringrealemotiontoyourvoice,withoutlosingthecontext.
Bringrealemotiontoyourvoice,withoutlosingthecontext.
Everything you need to generate, clone, and manipulate voice with state-of-the-art AI models.
Turn text into natural, expressive speech with state-of-the-art AI models.
Clone any voice from a few seconds of audio. Studio-quality, accent-aware replicas.
Isolate vocals and instruments with precision. Studio-grade audio splitting.
Explore and use hundreds of high-quality AI voices. Find the perfect tone for any project.
Fine-tune every detail. Create a voice that's uniquely yours.
Clone your voice or generate speech in any language — from Hindi and Gujarati to Japanese and Spanish. Regional Indian languages included.
Yes. Tarang fully supports Hindi voice cloning and text-to-speech. You can clone your voice in Hindi or convert any text to natural Hindi speech using AI. Hindi is one of Tarang's flagship languages with high-quality output.
Tarang supports text-to-speech and voice cloning in over 100 languages, including English, Hindi, Gujarati, Tamil, Telugu, Bengali, Marathi, Kannada, Malayalam, Spanish, French, German, Japanese, Chinese, Korean, Arabic, and many more.
Yes. Tarang supports cross-lingual voice cloning. You can record your voice in one language and generate speech in any of 100+ supported languages while preserving your voice's unique characteristics, tone, and emotional quality.
Yes. Tarang supports a wide range of regional Indian languages including Hindi, Gujarati, Marathi, Tamil, Telugu, Bengali, Kannada, Malayalam, Odia, Panjabi, and more. This is a key differentiator — most global voice cloning tools do not offer this level of Indian language coverage.
Yes. Voices generated on Tarang are commercially cleared for YouTube channels, podcasts, audiobooks, and games. Tarang's expressive synthesis avoids repetitive, robotic cadences, complying fully with YouTube's authentic content and monetization policies.
Unlike traditional TTS engines that process isolated sentences and suffer from volume drops and tonal drift, Tarang's neural model evaluates multi-sentence context. It maintains consistent speaker identity, natural breathing intervals, and dynamic emotional prosody from start to finish.
Tarang uses context-aware neural synthesis to eliminate clause-boundary loudness clipping, vocal fatigue, and robotic inflection across long narratives without requiring manual SSML tags, backed by deep multilingual and regional voice modeling.
From voice preparation to high-fidelity audio synthesis.
Clean, segment, transcribe
Build a reusable voice profile
Synthesize with emotion control
Get studio-quality MP3 / WAV files
We're constantly improving Tarang based on your feedback. Tell us what features you'd like to see, what we can improve, or what didn't work for you. Your feedback goes directly to the team.
Have questions, feedback, or partnership ideas? We'd love to hear from you.