A plain block of text isn't enough when you're transcribing a conversation.
Transcribee uses speaker diarization to separate different voices into individual transcript segments. Instead of trying to work out who was speaking from context, you can follow the conversation speaker by speaker.
After transcription, rename the detected speakers with the participants’ actual names.
Speaker diarization is the process of determining when different people are speaking in a recording.
It is different from identifying someone’s identity from their voice. Transcribee separates the detected voices into speaker labels; you can then assign the appropriate names yourself.
For example:
This makes conversations considerably easier to read than a transcript where everyone’s words appear together.
Transcribee supports recordings with speaker detection for up to 10 speakers.
Record directly in Transcribee or import an existing audio or video file.
After transcription, rename detected speakers with the participants’ actual names.
Search the conversation rather than repeatedly listening to the audio.
Generate a concise summary, key topics and action items from the transcript.
Transcripts and summaries can be translated into other languages.
Record a conversation or import an existing recording.
Start the transcription.
Transcribee separates different voices into speaker-labelled segments.
Rename each speaker.
Edit, search, summarise, analyse or export your transcript.
Supported file types include MP3, M4A, WAV, OPUS, MP4 and MOV. Recordings can be up to 10 hours and 2.1 GB once the free recording-length restriction has been unlocked.
Speaker-labelled transcription can be useful for:
Record directly in Transcribee or import an existing audio or video file. Transcribee supports recordings with speaker detection for up to 10 speakers.
Transcribee separates different voices, but it does not identify someone’s real-world identity from their voice. Detected speakers receive labels that you can rename yourself.