The technology primarily responsible for converting speech to text is Automatic Speech Recognition (ASR). This system uses algorithms to analyze audio signals, converting spoken language into written text. ASR technologies often involve complex machine learning models trained on large datasets to recognize different dialects, accents, and speech patterns. Applications for speech-to-text conversion range from voice-activated assistants and transcription services to accessibility tools for individuals with hearing impairments, significantly enhancing user interaction and content creation capabilities.