Beyond Transcription: ASR Model Delivers Words, Emotion, and Intent in 200ms
SMRTR summary
Whissle's META-1 model goes beyond standard speech recognition by delivering transcription alongside emotion, intent, age, and gender data in a single pass at ~200ms — 9x faster than competing metadata solutions. Tested across 1,300 samples in four languages, adding a KenLM language model reduced word error rates by up to 3.6%, while AssemblyAI completely failed on non-English streaming, exposing a major gap in multilingual ASR reliability.
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