Speech-to-Text
Speech-to-text (STT), also called automatic speech recognition (ASR), is the technology that converts spoken audio into written text, enabling voice-based interaction with computers and AI systems.
Understanding Speech-to-Text
Speech-to-text has advanced dramatically with deep learning. Modern ASR systems like OpenAI's Whisper achieve human-level transcription accuracy across accents, languages, and acoustic conditions. This accuracy has made voice input viable for professional use cases beyond simple commands. Meeting transcription, voice note capture, voice-commanded task creation, and voice-driven AI assistants all depend on reliable STT. The combination of STT with LLM understanding creates truly natural voice interfaces where you speak naturally and the AI understands intent rather than parsing rigid voice commands.
How GAIA Uses Speech-to-Text
GAIA's voice agent component uses speech-to-text to enable hands-free interaction. You can dictate tasks, ask questions about your schedule, and issue commands verbally. The transcribed text is processed by GAIA's LLM for intent recognition and action execution. This is particularly useful for mobile use and for capturing tasks and notes while away from a keyboard.
Related Concepts
Text-to-Speech
Text-to-speech (TTS) is the technology that converts written text into synthesized spoken audio, enabling computers and AI systems to communicate verbally through natural-sounding voices.
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a branch of artificial intelligence that focuses on enabling computers to understand, interpret, generate, and respond to human language in a meaningful way.
Intent Recognition
Intent recognition is the process by which an AI system identifies the underlying goal or purpose of a user's input, enabling it to select the appropriate response or action rather than responding only to surface-level phrasing.
Multimodal AI
Multimodal AI refers to artificial intelligence systems that can process and generate multiple types of data, such as text, images, audio, and video, within a single model or integrated pipeline.
