Why Whisper Falls Short for Live Mobile Apps and When to Use Streaming ASR

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Whisper has become the default on-device speech-to-text model, excelling at batch transcription tasks like meeting notes and lecture recordings. However, its batch-oriented architecture causes noticeable delays of 300ms to 2 seconds when used in live, real-time scenarios, creating a poor user experience for voice agents and live captions. Developers typically work around this by using rolling-window or VAD-based streaming wrappers, but these introduce chunk boundary errors, inconsistent punctuation, and added latency. Native streaming ASR models, by contrast, are trained from the ground up to process continuous audio with limited lookahead, enabling smoother and faster transcription. The core distinction is architectural: Whisper is a batch model adapted for streaming, while true streaming ASR is purpose-built for real-time use cases.

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