Glossary
Speech-to-Text (STT)
Speech-to-text is the technology that converts spoken language in audio/video into written text, used for transcription, captioning, and content analysis.
In AI clipping, speech-to-text serves two purposes: generating accurate captions for the final clips, and providing a transcript for the AI to analyze when detecting viral moments.
AutoClip uses Deepgram for speech-to-text transcription, which provides word-level timestamps for precise caption synchronization and high accuracy across different accents and audio qualities.
Related Terms
Frequently Asked Questions
How accurate is AutoClip's transcription?
AutoClip uses Deepgram, an industry-leading STT provider, which delivers high accuracy across various audio conditions, accents, and content types.
Why is speech-to-text important for AI clipping?
The transcript is the primary input for viral moment detection. AutoClip's AI reads the full transcript to identify the highest-engagement segments — so transcription accuracy directly affects clip quality. Deepgram's word-level timestamps also power precisely synchronized captions.
Does AutoClip's speech-to-text work for non-English content?
Deepgram supports transcription for major languages. English has the highest accuracy. For non-English content, AutoClip can transcribe and generate captions, though accuracy may vary by language.
Put Speech-to-Text (STT) to Work
AutoClip handles the full pipeline — viral moment detection, 9:16 reframing, captions, and auto-posting. Start clipping for free.
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