Kannada speech-to-text
Transcribe and translate speech across 60+ languages with the speed and accuracy real-time experiences demand.
Leading voice teams build with Deepgram
Fast and accurate Kannada speech recognition for real-world audio
Get real-time Kannada speech-to-text in under 300 ms while maintaining high accuracy in noisy, accented, or overlapping conversations.
Kannada language overview
Speakers: 60 million total speakers
Regions: Karnataka (India), Tamil Nadu, Maharashtra, Andhra Pradesh, Telangana, and diaspora communities in the United States, Canada, Australia, Singapore, and Malaysia
Dialects: Southern, Northern, Central, and Coastal varieties, with modern standard based on the Mysore-Bangalore dialect
Writing system: Kannada script (abugida)
Language family: Dravidian
Kannada is widely used across Karnataka state and neighboring regions of India, making it a key language for call center operations, healthcare patient interactions, regional news transcription, e-learning platforms, legal documentation, and government services in one of India's major economic hubs.
Kannada speech-to-text capabilities
Diarization
Automatically detect and label who is speaking in multi-speaker Kannada conversations.
Smart formatting
Apply automatic capitalization, paragraphing, and clean transcript structure for Kannada text.
Search
Instantly find words or phrases inside long Kannada recordings without reprocessing audio.
Utterances
Segment streaming Kannada audio into real-time sentence-level units for voice agents.
Punctuation
Add accurate punctuation and capitalization to Kannada transcripts for easy reading.
Redaction
Automatically remove sensitive data like credit cards, phone numbers, and PII from Kannada transcripts.
Keyterm prompting for Kannada
Boost recognition of brand names, product terms, and domain-specific vocabulary in Kannada audio to improve keyword recall and transcript accuracy.
Voice AI that performs in the real world
Low latency. Effortless scale. Production-grade reliability. Everything you need to build and run real-time voice experiences.
Domain-aware speech
Understand specialized terminology, names, accents, and industry-specific language with production-grade accuracy.
Expressive voices
Give every interaction a natural, consistent voice that adapts its tone when the conversation changes.
Context-aware delivery
Carry meaning, tone, and conversational state across turns so agents listen and respond more naturally.
Scale beyond Kannada with one API
Start with Kannada speech-to-text, then expand to 45+ languages using the same API, models, and tooling.
FAQ
Speech-to-text (also called automatic speech recognition, or ASR) converts spoken Kannada audio into written text. Deepgram processes the audio signal, detects speech in real time, and returns structured transcript data through an API. Developers use it for applications like voice agents, call analytics, captioning, and searchable media.
Yes. Deepgram supports automatic speech recognition (ASR) for Kannada audio. You can transcribe real-time or prerecorded audio by setting `language=kn` in your API request.
Deepgram supports Kannada in the Nova model family. Model availability may vary by language, so check the Models & Languages page for the latest support details.
Yes. Deepgram provides low-latency streaming transcription for Kannada, suitable for live voice agents, call analytics, captioning, and other real-time applications.
Deepgram offers automatic language detection for many languages. You can enable it with `detect_language=true`. See the Language Detection documentation for the full list of supported languages.
Yes. Deepgram supports multilingual transcription and code-switching when using Nova's multilingual models. Set `language=multi` to enable it. See the Models & Languages page for supported languages.
Deepgram supports timestamps, punctuation, diarization, numeral formatting, filler-word detection, redaction, and more — all through the API.
Accuracy depends on model choice, audio quality, and domain. Nova models deliver state-of-the-art accuracy, and you can improve results further using Keyterm Prompting or Custom Models.
Sign up for a free Deepgram account to access your API key. You can test Kannada transcription instantly in the Playground, or call the API directly by sending audio to `/v1/listen` with `language=kn`. Starter apps and code examples are available on GitHub.
Ready to build with Kannada speech-to-text?
Start transcribing Kannada audio with Deepgram's speech-to-text API. It is fast, accurate, and built for real-time applications.
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