Transcription
Transcription is the process of converting spoken audio into written text. In AI clip generators, transcription is the foundation step — every other feature (auto-captions, viral-clip scoring, semantic search across the source) depends on accurate transcription. Modern speech-to-text models hit 95%+ accuracy on clear English audio with native speakers.
Transcription quality varies with three input factors. (1) Audio quality — clean audio recorded with a directional mic outperforms ambient room audio dramatically. (2) Speaker clarity — heavily-accented or mumbled speech reduces accuracy by 5-15 percentage points. (3) Domain vocabulary — technical jargon, brand names, and proper nouns trip generic models that haven't seen them in training.
The practical implication for AI clip generators: the quality of clip selection is bounded by the quality of transcription. A misheard word in the transcript means the viral-clip scorer might miss the moment that word landed, or worse, score a misheard segment that doesn't actually exist as said. Always do a per-word caption pass before publishing — it's the cheapest quality gate available.
Clipzing.com supports 30+ languages for transcription. English is highest-accuracy; less-resourced languages run lower. The caption editor lets you fix per-word transcription errors quickly without re-running the pipeline.
Related terms
Auto-captions
Auto-captions are AI-generated subtitles that transcribe spoken audio into on-screen text in real time during video playback. In short-form video, auto-captions are mandatory — roughly 85% of social feed playback happens with sound off, and uncaptioned clips lose retention immediately. Modern auto-caption quality on English audio runs 95%+ accurate.
Viral score
A viral score is an AI-generated numerical estimate of how likely a candidate video clip is to perform on short-form platforms. AI clip generators compute viral scores by analyzing multiple signals — speech cadence, hook strength, length, visual cuts, emotional peaks — and ranking candidate clips so creators publish the highest-scoring ones first.
Aspect ratio
Aspect ratio is the proportional relationship between a video's width and height, expressed as width:height. The dominant short-form ratio in 2026 is 9:16 (vertical, 1080×1920) used by TikTok, Instagram Reels, and YouTube Shorts. Long-form video uses 16:9 (1920×1080). Square 1:1 is used by LinkedIn and Instagram feed.
Auto-reframe
Auto-reframe is an AI feature that converts a video from one aspect ratio to another by tracking the subject (typically the active speaker's face) across frames and re-cropping the output to keep the subject centered. The dominant use case is converting 16:9 source footage into 9:16 vertical clips for TikTok, Reels, and YouTube Shorts.