About Muse Voice: A Review-First Transcription Workspace
A speech to text product for people who must inspect, correct, and reuse the result—not merely generate it.
Why the workspace exists
Audio preserves a conversation, but it is slow to search and difficult to hand off. Automatic recognition removes the blank page; it does not verify names, identify every voice correctly, or decide whether the next deliverable is a document, caption file, or data record.
Muse Voice connects those steps. A file, live browser capture, or media URL becomes timed segments that you can check against the source, edit, label, and export without rebuilding the transcript elsewhere.
The four stages Muse Voice covers
Each capability supports a specific decision between recorded speech and an approved output.
Record or upload
Choose an audio or video file up to 1 GB, make a browser recording, or import a supported hosted-media address.
About 100 languages
Use language detection when the source is unknown, or specify the expected spoken language before processing.
Edit and label
Return to a timed passage, find text by search, correct recognition errors, and apply a reviewed name to a speaker's segments.
Export anywhere
Generate TXT, DOCX, PDF, SRT, VTT, or JSON from the transcript after your corrections have been applied.
Recognition and speaker processing
Muse Voice uses OpenAI Whisper for speech recognition and can apply speaker diarization when a recording contains several voices. Both operations run on our servers. The editor remains necessary because automatic output can still mishear names, jargon, overlapping speech, or unclear audio.
Recording storage and control
Uploaded audio is processed to create the requested transcript. We do not sell recordings or use them to train models. A file and its transcript remain available in the account until the user deletes that recording, which removes both.
Read our Privacy PolicyWho benefits from a reviewable transcript
Creators
Podcasters and video producers who review one transcript before developing captions, show notes, or written adaptations.
People working with source recordings
People who need to locate a passage in a long recording and verify an interview quotation or lecture note against its source.
Teams
Groups that need a searchable meeting record with speakers, decisions, and commitments reviewed in context.
Principles behind the workflow
Privacy first
People who submit recordings retain control of the source and resulting transcript.
Accessible by default
The interface is designed for keyboard navigation, screen readers, and legible transcript review.
Always improving
Product changes are informed by recognition updates and concrete failure cases reported by users.
Questions or feedback?
Describe the source, the intended outcome, and the point where the workflow failed so we can investigate useful context.