Transcription accuracy on a clean studio recording is a solved problem. Accuracy on a 8kHz mobile call from a moving auto-rickshaw, in Hinglish, is not. Deepgram is tuned for the second case, which is the one that actually happens.
Deepgram is a speech recognition platform built for real-time streaming transcription rather than batch processing of recorded files. Its Nova-3 model transcribes code-switching conversations live across ten languages including Hindi, and Deepgram reports a 54.2% reduction in streaming word error rate against compared competitors — with the largest gains on languages like Hindi, where compound words, heavy inflection and non-Latin script had been the weak point.
In a classic voice pipeline, ASR is the first link and every error propagates. If 'teen baje' is transcribed as 'tin badge', no amount of downstream model quality recovers the call. Indian phone audio is a genuinely hard case: compressed codecs, background noise, wide accent variation and constant code-switching. Deepgram is the engine that holds up on it.
What you get, stated plainly enough to check.
Four steps, none of which involve writing telephony code.
Deepgram is chosen per agent as the transcription layer in a classic STT plus LLM plus TTS pipeline.
Declaring Hindi, English or code-mixed input up front measurably improves accuracy over letting the engine guess.
Vomyra uses partial transcripts to start forming a response before the caller has finished, which shortens the pause.
Every call is transcribed and searchable, so objection analysis and QA run on text rather than on audio review.
Phone audio is compressed and narrowband. An engine tuned on clean recordings degrades exactly where your calls live.
Indian callers switch language mid-sentence. Deepgram holds accuracy across the switch rather than resetting at it.
Partial transcripts stream back in milliseconds, letting the agent start reasoning before the caller has finished the sentence.
Yes. Nova-3 transcribes code-switching conversations in real time across ten languages including Hindi and English, which is exactly the Hinglish case — frequent English switching inside inflection-heavy Hindi. Beyond Hindi it also covers Bengali, Marathi, Tamil, Telugu and Gujarati.
Because its models are trained on telephony-band audio rather than broadcast-quality recordings. Phone audio is narrowband and compressed, so engines benchmarked on clean speech degrade precisely where real calls sit. Add background noise and accent variation and the gap widens.
Not for the conversation itself — an S2S model like Nova 2 Sonic hears the audio directly with no transcription step. You may still want Deepgram running for exact word-level transcripts where compliance requires a verbatim record.
Interim results return in milliseconds, and Vomyra uses those partial transcripts to start forming the response before the caller has finished speaking — which is a large part of why turns feel natural rather than stilted.
Yes. Bring your own key and pay Deepgram directly for usage, with Vomyra charging only the platform fee. Managed access included on your Vomyra plan is the zero-setup alternative.