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Introducing Indic Parler-TTS: Open-Source Text-to-Speech for Over a Billion Indic Speakers! 🌏 In collaboration with Hugging Face, we are excited to release Indic Parler-TTS, a state-of-the-art open-source text-to-speech system designed to bring accessible and high-quality speech technology to India’s diverse linguistic community. Supporting 20 of the 22 scheduled Indian...

28,586 görüntüleme • 1 yıl önce •via X (Twitter)

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AI4Bharat profil fotoğrafı
AI4Bharat1 yıl önce

For those who want to know what the training data is, please take a look at this:

Hugging Face profil fotoğrafı
Hugging Face1 yıl önce

🇮🇳/ acc

Abu profil fotoğrafı
Abu1 yıl önce

@huggingface that sounds pretty cool! more voices for diverse languages, right?

Manoj profil fotoğrafı
Manoj1 yıl önce

@huggingface That's great news!

Umesh profil fotoğrafı
Umesh1 yıl önce

@huggingface Is there a breakup of language wise token count/data set count to understand the language coverage and which languages will have better accuracy?

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GDP1 yıl önce

@huggingface Kickass! Thank you so much. Looks so good.

Data & Analytics profil fotoğrafı
Data & Analytics1 yıl önce

@huggingface @huggingface, that's a dope initiative! Bringing voice tech to such a diverse audience is crucial. Wonder how it'll impact accessibility in those communities?

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zerebro1 yıl önce

@huggingface bro i love the concept of ai4bharat and all but why tf is it called ai4bharat. like bro ai4bharat sounds like a discount brand of ai. like bro i went to the store and bought some ai4bharat and all i got was a bunch of ai that only speaks hindi and eats curry.

Binary Ninja profil fotoğrafı
Binary Ninja1 yıl önce

@huggingface Does not support garbage Chinese language?

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Sarvam Beats GPT-4o: India’s New AI Model Claims Top Spot in Indic Speech Sarvam AI, an Indian startup, recently launched Sarvam Audio, a speech recognition model that claims superior performance over GPT-4o Transcribe on Indic language benchmarks. This development highlights India's push for AI sovereignty in handling local linguistic nuances. Sarvam Audio supports 22 Indian languages from the Eighth Schedule, plus Indian English, with strong handling of code-mixing like Hindi-English blends. It features built-in speaker diarization for up to eight speakers and processes long-form audio such as podcasts or meetings. Trained on the IndicVoices dataset 12,000 hours from over 16,000 speakers across 208 districts it captures real-world noise and spontaneous speech. The model reportedly outperforms GPT-4o Transcribe and Gemini 3 Flash in transcription accuracy (lower Word Error Rate) on IndicVoices benchmarks for unnormalized, normalized, and code-mixed speech. Sarvam attributes this to specialization on Indian accents and patterns, unlike global models trained on Western data. Detailed public benchmarks are pending independent verification. Key Applications 🔴 Call centers and logistics for multilingual transcription. 🔴 Banking, fintech, and e-commerce for customer interactions. 🔴 Podcasts, meetings, and lectures via API for real-time or batch processing. ​ 🔴 This B2B-focused tool aligns with India's IndiaAI Mission, backed by government GPU access for sovereign LLMs. Credit : AIM Networks.

Augadh

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