Audio & Realtime Speech Models

Processing retrieved audio streams entirely on the client allows dialogue to be placed spatially within 3D environments and enhanced with native real-time effects like reverb, pitch-shifting, equalizers, and tape delay.

STD.DEV helps brands programmatically generate custom, localized, and expressive brand voices on demand by leveraging Retrieval-Augmented Generation (RAG) pipelines to synthesize steerable narratives.

STD.DEV's streaming speech-to-text models process multi-speaker speech with sub-second latency and are equipped with custom vocabulary mapping and speaker diarization to transcribe vocal inputs into formatted text.

The Wasm-based VAD module avoids continuous audio network streaming by calculating silences and voice onset locally on the user's device, triggering cloud-based STT and TTS models only when active speech is detected.

Brands can engage global audiences by deploying ultra-low latency, multilingual conversational agents and interactive installations that support real-time vocal exchange in over 70 languages without text latency.

The business advantage is eliminating traditional studio recording overhead by programmatically generating custom, localized, and expressive brand voices on demand.

STD.DEV's advanced streaming Speech-to-Text (STT) models transcribe vocal inputs into formatted text with sub-second latency, enabling real-time semantic search indexing and interactive media controls.

The underlying principle is to execute silences and voice onset calculations locally on the user's device using a Wasm-based Voice Activity Detection (VAD) module, only triggering cloud services when active speech is detected.

Audio and speech models enable natural, real-time vocal interaction by combining native audio reasoning with sub-second streaming latencies.