What is automatic speech recognition (ASR)?
ASR is technology that converts spoken language into written text using AI models. Also called speech-to-text (STT), modern ASR systems use deep neural networks to turn an audio waveform into a transcript. ASR is the listening layer behind voice assistants, meeting transcription, live captioning, dictation tools, contact-center analytics, and conversational voice agents.
What is an example of ASR?
Voice assistants transcribing commands like “Set a reminder for tomorrow” rely on ASR. Other everyday examples include live captions on video calls and streaming platforms, meeting transcription tools, video subtitle generation, call-center transcription and analytics, and the first stage of every voice AI agent - where ASR converts caller speech into text that a language model can respond to before a TTS system speaks the reply.
How does ASR work?
ASR uses acoustic and language models to interpret incoming audio, segment phonemes, and assemble accurate text outputs.
How does ai-coustics help ASR?
ai-coustics models are optimized specifically to improve ASR performance. Quail model family is trained to enhance the acoustic cues (for example by reducing noise and reverb) that matter for machine understanding - lowering Word Error Rate and delivering more reliable transcripts for voice agents, and Voice AI.
