Chariot releases Chariot-1-ASR Realtime, supporting real-time speech recognition in 10 Indian languages
Chariot released the real-time speech recognition model Chariot-1-ASR Realtime on October 22, supporting 10 Indian languages including Hindi, Marathi, Bengali, and Tamil, as well as Indian English, and it is now available on the Chariot platform. The company says it tested on 79 public test sets and about 153,000 recordings; in batch mode the error rate is 26% lower than Google Gemini 3.5 Transcribe and 9% lower than Sarvam Saaras v4; in streaming mode it is 17% lower than Sarvam Saaras v4 and 57% lower than ElevenLabs Scribe v2 Realtime, and these results all come from Chariot's self-testing. The model offers balanced and high-accuracy modes, can automatically identify the language, and supports writing borrowed English words in English letters or the corresponding language's script.
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Chariot publishes self-test data comparing with systems such as Gemini and Sarvam, allowing readers to judge the accuracy level of real-time transcription for Indian languages.
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Chariot, a frontier AI research lab, launched Chariot-1-ASR Realtime on October 22, a speech recognition model that converts spoken words into text while people are still talking. The company said the model outperformed every streaming and batch transcription system it tested across 10 Indian languages.
The model supports Hindi, Marathi, Bengali, Tamil, Telugu, Kannada, Malayalam, Gujarati, Punjabi and Odia. It also supports Indian English and is available on the Chariot platform, according to the company.
Chariot said it tested the model on 79 public test sets from 11 collections, covering around 153,000 audio recordings. The tests included everyday conversations, telephone calls, read-aloud speech and recordings with background noise.
The research lab said its model made 26% fewer errors than Google Gemini 3.5 Transcribe and 9% fewer than Sarvam’s Saaras v4 when compared with systems that process an entire recording before producing text.
In tests against systems that transcribe speech as it arrives, Chariot reported 17% fewer errors than Sarvam Saaras v4, 34% fewer than Google Gemini 3.5 Transcribe Live and 57% fewer than ElevenLabs Scribe v2 Realtime. Chariot was not told which language was being spoken during these tests, while competing systems were given the language settings that worked best for them.
On Monsoon, a public collection of unscripted telephone conversations, Chariot reported an error rate of 5.04% on Hindi calls, compared with 8.27% for OpenAI’s gpt-transcribe. On Indian English calls, its 3% error rate matched results from Microsoft Azure Speech and Zoom Scribe v2 Pro on the Open ASR Leaderboard.
The company also reported a 17.21% error rate on Vaani, a collection of Hindi recordings from speakers across different districts. Sarvam Saaras v4 recorded 17.86% on the same test. Lower error rates indicate more accurate transcription.
These results come from Chariot’s own tests.
Chariot-1-ASR Realtime offers two modes. The balanced mode produces text faster for applications such as voice assistants and live captions. The high-accuracy mode considers more audio before producing text, making it suitable for call transcripts, meeting notes, and dictation.
The model can identify the language automatically or use a language selected by the application. It can also write borrowed English words in either the English alphabet or the script of the language being spoken.
“Speech recognition has always made you choose: fast or accurate. For Indian languages, Chariot-1-ASR Realtime ends that choice,” Chariot co-founder Parth Sarthi said.
The model is based on Chariot-1, the company’s broader speech model, which has been adapted for transcription. Chariot said it plans to use the same underlying model for other speech tasks, including generating speech and identifying languages.