Descript is an AI-powered video and audio editor that lets you cut recordings by editing their transcript, then clean up, caption, translate and repurpose the result. Underlord, its AI co-editor, plus Studio Sound, voice cloning and screen recording turn a single tool into a full production pipeline for creators and teams.
Descript is an AI-powered video and audio editor that lets you cut recordings by editing their transcript, then clean up, caption, translate and repurpose the result. Underlord, its AI co-editor, plus Studio Sound, voice cloning and screen recording turn a single tool into a full production pipeline for creators and teams.
Text-based editing
Edit audio and video by deleting, rearranging or retyping words in the automatic transcript, with a full multitrack timeline available when you need it.
Underlord AI co-editor
Describe the edit you want in plain language and let the AI assistant assemble a tight cut, add clips and handle repetitive production work.
Studio Sound and speech regeneration
Remove background noise, level out voices, and fix misread lines with Regenerate Speech using a clone of your own voice.
Captions, translation and clip export
Generate subtitles and transcripts in a click, translate video into other languages, and reformat long recordings into shareable vertical clips.
优势与优点
+Editing video by editing a transcript is dramatically faster than timeline scrubbing for interview, podcast and talking-head content
+Audio and visual AI features (Studio Sound, Eye Contact, Green Screen, Regenerate Speech) cover fixes that would otherwise need several tools
常见问题：Descript 对比 WAAS（Whisper as a Service）
Descript 有 3,267,817 月访问量，而 WAAS（Whisper as a Service）有 0。流量估算描述的是受众规模，而非产品质量。
Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
