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Multimodal
Speech-to-Text AI
Definition
Speech-to-text (STT) AI converts spoken audio into written text using models like Whisper and Deepgram, enabling transcription, voice interfaces, and accessibility features.
Why It Matters
Speech-to-text enables voice interfaces for applications, automated transcription of meetings and podcasts, accessibility for hearing-impaired users, and voice-driven AI agents. Modern STT has become accurate enough for production use across many languages and accents.
Key Solutions
API Services:
- OpenAI Whisper API: High accuracy, 50+ languages
- Deepgram: Real-time, enterprise features
- AssemblyAI: Specialized features (speaker ID, sentiment)
- Google Speech-to-Text: Google Cloud integration
Self-Hosted:
- Whisper (local): Open-source, free, private
- faster-whisper: Optimized Whisper implementation
- Vosk: Lightweight offline recognition
Key Features to Consider
- Accuracy: Word error rate for your content type
- Latency: Real-time vs batch processing
- Languages: Support for your target languages
- Speaker Diarization: Who said what
- Punctuation: Automatic formatting
- Custom Vocabulary: Domain-specific terms