Definition
Speech-to-text, also known as Automatic Speech Recognition (ASR), is AI technology that converts spoken language into written text. Modern ASR systems use deep learning models trained on vast amounts of multilingual audio data to achieve high accuracy even with diverse accents, background noise, and domain-specific vocabulary. In video editing, speech-to-text powers auto-captioning, searchable transcripts, text-based editing (editing video by editing text), content analysis, and SEO optimization through indexable text content.
How Loopdesk Uses This
Loopdesk's speech-to-text engine supports 57 languages and powers multiple features: auto-captioning, searchable transcripts, silence/filler detection, and natural language editing. The transcript becomes an interactive editing interface — you can edit your video by editing the text, and Loopdesk translates text changes into timeline edits automatically.
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Auto-Generated Captions (Auto Subtitles)
AI-powered speech-to-text technology that automatically generates synchronized captions and subtitles for video content.
Speaker Detection (Speaker Diarization)
AI's ability to identify and distinguish between different speakers in audio and video content.
Natural Language Editing
Editing videos by typing or speaking instructions in plain English, which AI interprets and executes on your timeline.