What is Speech to Text (STT)?
Speech to text, also called speech recognition or STT, is the technology that converts spoken language into written text. It is the first step in any voice AI pipeline, turning raw audio from a phone call or microphone into text that NLU systems can process.
How Speech to Text (STT) works
Modern STT engines use deep learning models trained on thousands of hours of speech data. They process audio in small chunks (typically 20 to 40 millisecond frames), predict phonemes, and assemble them into words and sentences. Indian language STT faces additional challenges: background noise on mobile calls, code switching between languages, and dialect variation within a single language.
Why Speech to Text (STT) matters for enterprise
STT accuracy directly determines voice AI quality. A 95% accurate STT system means 1 in 20 words is wrong, which compounds across a full conversation. Enterprise grade systems need 97%+ accuracy in production telephony conditions (8kHz audio, background noise, accents).
How ARCA handles Speech to Text (STT)
ARCA's STT pipeline is optimized for Indian telephony audio, handling 22 Indian languages including code switching between them without requiring the caller to select a language upfront.
See how ARCA uses speech to text (stt) in practice.
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