Why the Next Leap in Speech AI Comes from Kalpa Labs

In recent years, large language models (LLMs) have unified a wide range of text-based tasks under a single architecture. One model can code, translate, summarise and generate with remarkable fluidity. This unification, however, has not yet reached the world of speech. Existing models are either fast but inaccurate or accurate but slow, largely due to high token usage—50 tokens per second—and fixed input padding, which increases computing costs. Speech-focused AI startup Kalpa Labs focuses on creating fast, multilingual, real-time speech-to-text models that resolve the latency and inefficiency issues of systems like Whisper.  Kalpa Labs aims to reduce audio token rates, eliminate unnecessary padding with configurable “register” tokens and use sparse architectures like mix