Multispeaker Transcription

Upload a recording with several speakers, or record it live, and get a transcript with each speaker labeled and timestamped.

MP4, WebM, MOV, AVI, MKV, WMV, and FLV. Free to try, up to 45 minutes. No install.

Or paste a video link

YouTube, TikTok, Instagram, Vimeo, Google Drive, Dropbox, direct links

Recordings are encrypted in transit and at rest and are not used to train AI models. Privacy · Security

Speaker Identification AI Notes and Chat Multiple Export Formats

Transcribe a Recording with Multiple Speakers, Get Each One Labeled

Upload a recording with several people talking, or paste a link, and ScreenApp turns it into a transcript with each speaker labeled and a timestamp on every line. Record the conversation live with the browser recorder or the iOS and Android apps, or connect the meeting bot for Zoom, Google Meet and Microsoft Teams for a call, then upload the file when you have one.

A labeled transcript replaces re-listening to a recording to work out who said what.

What you get:

How to Transcribe Multiple Speakers

  1. Upload or paste a link: Drag in the audio or video file (MP4, WebM, MOV, AVI, MKV, WMV, and FLV), or paste a link. No account setup is needed to start.
  2. Let it transcribe: The audio is converted to text and each person is split into their own speaker label, with a timestamp on every sentence.
  3. Review and export: Read the transcript in the browser, rename a speaker label if needed, and export as PDF, DOCX, TXT, SRT and VTT.

Accuracy depends on the audio and the language spoken. 25 of the 99 supported languages carry word-level speaker diarization; the rest transcribe to text without per-speaker labels. A single microphone with participants close by and limited cross-talk also gives the clearest split between speakers. See how we measure accuracy.

Multi-Speaker Transcription vs Other Apps

FeatureScreenAppOtter.aiRevSonix
Free planone recording, up to 45 min300 min/month45 min/month (AI)30-min trial
Speaker identificationIncludedBasicIncludedIncluded
Speaker renameclick a speaker label to rename it, match it to a team member, or reassign a single segmentNot statedNot statedNot stated
AI notesIncludedPro, $8.33 to $16.99/monthNot statedNot stated
Export formatsPDF, DOCX, TXT, SRT and VTTmp3, txt, pdf, docx, srt (Pro, Business and Enterprise plans, with bulk export)Not statedDOCX, PDF, TXT, SRT, VTT
Languages996Not stated54+
Paid plan$19/month annual$8.33/month annual$25.49/month annual$25/month

Sources, checked 2026-09-13: screenapp.io/accuracy#languages, github.com/screenappai/screenapp-new/blob/main/apps/web/src/app/api/files/[id]/transcript/export/route.ts, screenapp.io/pricing, screenapp.io/help/how-many-minutes-can-i-record, otter.ai/pricing, rev.com/pricing, sonix.ai/pricing, screenapp.io/help/how-to-edit-speaker-labels

  • vs Otter.ai: Otter’s free plan caps you at 300 minutes a month, and its speaker identification tier on the free plan is Basic. ScreenApp includes speaker labels on every plan and lets you rename a label after the fact.
  • vs Rev: Rev’s free tier gives 45 AI minutes a month, then charges $0.25 per minute for an AI transcript or $1.99 per minute for a human one. A recurring series of multi-speaker recordings adds up fast at either rate.
  • vs Sonix: Sonix gives a one-time 30-minute trial, then a $25-a-month plan. ScreenApp’s free plan renews rather than being a one-time trial.

Who Uses Multi-Speaker Transcription

Journalists transcribe interviews and panel discussions with several sources, then quote each speaker directly with a timestamp for fact-checking.

Podcast producers transcribe episodes with a host and multiple guests, splitting the conversation by speaker to pull show notes and clips.

Researchers transcribe group interviews and focus groups, then read the transcript by speaker to see how each participant answered.

Recruiting and HR teams transcribe panel interviews with several interviewers and a candidate, so anyone reviewing the file later can see who asked what.

Legal and compliance teams transcribe depositions, multi-party calls, and recorded statements where knowing which person said which line matters.

Documentary and video teams transcribe interview footage with more than one subject, using the speaker labels to log who is on camera at each point.

FAQ

What does “speaker identification” mean in a transcript?

It means the transcript marks who is speaking at each moment, so instead of one block of text you get separate, labeled lines for each person.

How does ScreenApp identify speakers?

speaker identification splits the audio into separate voices and labels each one in the transcript, in 99 languages.

Does speaker identification work in every language?

No. Word-level speaker diarization runs on 25 of the 99 supported languages, marked with a dagger on the language list. Recordings in the other languages still transcribe to text, without per-speaker labels.

Can I rename the speaker labels?

Yes. click a speaker label to rename it, match it to a team member, or reassign a single segment.

How does ScreenApp handle people talking over each other?

overlapping speech can confuse the diarization system. A single, central microphone with limited cross-talk gives the clearest split between speakers.

Does ScreenApp reduce background noise before transcribing?

No. ScreenApp does not apply noise reduction. A quieter recording environment and a microphone placed close to the speakers produces a cleaner transcript than a noisy room.

Can I export a multi-speaker transcript?

Yes, as PDF, DOCX, TXT, SRT and VTT, with the speaker labels and timestamps kept in the exported file.

Can I ask questions about what a specific speaker said?

Yes, AI chat with any recording lets you ask about the discussion and get an answer that points to the moment in the recording, including who said it.

Is a multi-speaker recording kept private?

Recordings are encrypted in transit and stored with AES-256, on SOC 2 Type 2 infrastructure, and are not used to train AI models. Security controls are published on the trust center.

FAQ

What does "speaker identification" mean in a transcript?

It means the transcript marks who is speaking at each moment, so instead of one block of text you get separate, labeled lines for each person.

How does ScreenApp identify speakers?

speaker identification splits the audio into separate voices and labels each one in the transcript, in 99 languages.

Does speaker identification work in every language?

No. Word-level speaker diarization runs on 25 of the 99 supported languages, marked with a dagger on the language list. Recordings in the other languages still transcribe to text, without per-speaker labels.

How does ScreenApp handle people talking over each other?

overlapping speech can confuse the diarization system. A single, central microphone with limited cross-talk gives the clearest split between speakers.

Does ScreenApp reduce background noise before transcribing?

No. ScreenApp does not apply noise reduction. A quieter recording environment and a microphone placed close to the speakers produces a cleaner transcript than a noisy room.

Can I export a multi-speaker transcript?

Yes, as PDF, DOCX, TXT, SRT and VTT, with the speaker labels and timestamps kept in the exported file.

Can I ask questions about what a specific speaker said?

Yes, AI chat with any recording lets you ask about the discussion and get an answer that points to the moment in the recording, including who said it.

Is a multi-speaker recording kept private?

Recordings are encrypted in transit and stored with AES-256, on SOC 2 Type 2 infrastructure, and are not used to train AI models. Security controls are published on the trust center.

First-party usage data

2,152,711

speakers identified

across all transcribed recordings to date. Pulled at build time from the ScreenApp production database. Methodology: see the accuracy page.

First-party production data

What ScreenApp users actually record

Top content types across 77,528 labelled recordings in the last 90 days. Pulled at build time from videometainfo.meetingType in production. Methodology: accuracy page.

15,376

podcast

19.8% of labelled

15,150

call

19.5% of labelled

14,724

training

19.0% of labelled

13,238

meeting

17.1% of labelled

11,391

lecture

14.7% of labelled

3,175

presentation

4.1% of labelled

3,107

webinar

4.0% of labelled

1,367

interview

1.8% of labelled

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