MODEL PROFILE

tara

Trelis · tara

**Tara is a frontier automatic speech-recognition model for Hindi and mixed-code (Hinglish) transcription.** On the AI4Bharat Vistaar Hindi benchmark suite it achieves state-of-the-art aggregate accuracy, outperforming leading commercial Hindi ASR systems on the 7-benchmark Vistaar mean, while natively handling Hindi–English code-switched speech through a dedicated **mixed-code mode** that renders English words in Latin script and Hindi in Devanagari, the way real Hinglish is written. The mixed-code mode (the ` ` prefix above) conditions generation only: on pure-Hindi audio it neither degrades accuracy nor forces transliteration; on mixed-code audio it renders English words in Latin script. Evaluation code, the exact text normalizer, and Tara's per-utterance predictions for every benchmark below are published at TrelisResearch/tara, so all numbers can be reproduced or re-scored under alternative normalizers.

Speech recognitioncode-switchinglicense:apache-2.0
Context windowNot disclosed
Input → OutputAudio → Text
Model weightsNot verified
Profile updated2026/10/31 04:09:01
OVERVIEW

Model overview

**Tara is a frontier automatic speech-recognition model for Hindi and mixed-code (Hinglish) transcription.** On the AI4Bharat Vistaar Hindi benchmark suite it achieves state-of-the-art aggregate accuracy, outperforming leading commercial Hindi ASR systems on the 7-benchmark Vistaar mean, while natively handling Hindi–English code-switched speech through a dedicated **mixed-code mode** that renders English words in Latin script and Hindi in Devanagari, the way real Hinglish is written. The mixed-code mode (the ` ` prefix above) conditions generation only: on pure-Hindi audio it neither degrades accuracy nor forces transliteration; on mixed-code audio it renders English words in Latin script. Evaluation code, the exact text normalizer, and Tara's per-utterance predictions for every benchmark below are published at TrelisResearch/tara, so all numbers can be reproduced or re-scored under alternative normalizers.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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Frequently asked questions

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。