Hindi Speech to Text
Convert Hindi (हिन्दी) audio to text with AI. Fast, accurate, open models.
Best Models for Hindi
| Model | Provider | WER | Speed | |
|---|---|---|---|---|
| STT.ai Enhanced Best | OpenAI (hosted by STT.ai) | 4.2% | Paid tier | |
| Whisper Large V3 | OpenAI | 4.2% | Paid tier | |
| Whisper Turbo | OpenAI | 5.1% | Try it |
About Hindi Transcription
Hindi is the third most spoken language globally. STT.ai provides accurate Hindi transcription including handling of code-switching with English (Hinglish).
STT.ai provides state-of-the-art Hindi speech recognition powered by multiple AI models. Whether you need to transcribe interviews, lectures, podcasts, or meetings in Hindi, our platform automatically detects the language and selects the optimal model for the best accuracy.
How Accurate is Hindi Transcription?
Accuracy for Hindi transcription depends on audio quality, speaker clarity, background noise, and the model you choose. On clean audio with a single speaker, our best models achieve a Word Error Rate (WER) under 6% for Hindi -- approaching human-level accuracy.
For the best results with Hindi audio, we recommend:
- Clear audio -- minimize background noise and use a good microphone
- Single speaker segments -- enable speaker diarization for multi-speaker recordings
- Choose the right model -- Whisper Large V3 is the most accurate and has the broadest language coverage; Whisper Turbo trades a little accuracy for speed
- Specify the language -- while auto-detect works well, manually selecting Hindi can improve accuracy slightly
Export Formats for Hindi Transcripts
After transcribing your Hindi audio, download the result in any of these formats:
TXT
Plain text transcript
SRT
Subtitles with timestamps
VTT
Web video captions
DOCX
Word document
JSON
Structured data with timestamps
PDF
Print-ready document
Frequently Asked Questions
Upload an audio or video file containing Hindi (हिन्दी) to STT.ai or paste a URL. Select a model that supports Hindi — for best results pick the one with the lowest WER on the table above — and click Transcribe.
Yes. STT.ai gives every visitor 600 free minutes to start, which includes Hindi (602 million speakers worldwide). No signup required for your first file. Paid plans starting at $5/month unlock longer files and private transcripts.
Hindi accuracy on clean audio reaches 88-93% with our best models. Indic-script output preserves matras and conjunct consonants; transliteration to Latin is also available as a post-processing option.
The table above ranks the models by WER (lower is better). For Hindi, Whisper Large V3 has the broadest coverage and the best accuracy; Whisper Turbo trades a little accuracy for speed. STT.ai Enhanced is Whisper Large V3 on our GPU, included with paid plans.
Yes. Hindi (हिन्दी) output preserves matras, anusvara, and conjunct consonant clusters. Romanized transliteration is available as a post-processing option for downstream use.
Yes. Speaker diarization is language-agnostic and works on Hindi the same way it does on English. Each speaker is labeled (Speaker 1, Speaker 2, ...) and you can rename them in the editor after transcription.
Most Hindi files are transcribed in under 5 minutes. A 1-hour Hindi audio file typically takes 2-3 minutes with our fastest models, and slightly longer with the highest-accuracy models.
Hindi files in MP3, WAV, M4A, FLAC, OGG, MP4, MKV, MOV, WebM, AVI, and 10+ other formats all work. Output to TXT, SRT, VTT, DOCX, JSON, and PDF — all with Hindi text intact.
Yes. Hindi audio files are processed and deleted by default. Pro plans add client-side encryption — even if our database is breached, your transcripts are unreadable without your key. Hindi data is never used for model training without explicit opt-in.
Yes. Export the transcript as SRT or VTT — both work with YouTube, Vimeo, TikTok, and all major video platforms. Burn-subtitles tool overlays them onto video as hardsubs.
Yes. After transcribing Hindi, the subtitle-translator tool can translate the SRT/VTT to any of 100+ target languages. Useful if your Hindi content needs subtitles for a wider audience.
Yes. The REST API supports Hindi via the language parameter (auto-detect is also available). Python and Node.js SDKs let you batch-transcribe Hindi audio with full timestamps and speaker labels.
For Hindi, the biggest accuracy variables are background noise, overlapping speakers, and accent strength. Use a good microphone, separate speakers when possible, and pick a model trained on the relevant dialect.