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އިންތަރްވިޔޫ ތިރާނުސްކިރިޕްސަން.އިತުރި ރެކޮރްޑިނާ، ނިވާ ރেজަލްޓް.

Phone memo، Zoom call، lavalier rig، ނުވަތަ handheld field recorder — interview recording ފޭސް، speaker-labeled، timestamped ޓެކްސް ތި ވތާ ކަވެ.

Drop a file, or pick one

MP3 · WAV · M4A · MP4 · MOV · MKV · OGG · OPUS · FLAC · WEBM — up to 100 MB anonymously

Paste a link, we’ll fetch the audio

YouTube · TikTok · Vimeo · Twitter · SoundCloud · Spotify · 50+ more

Record straight from your browser

Sign up takes 30 seconds — recording opens right after, in the dashboard.

No card required~90s per 60-min fileSRT · VTT · DOCX · TXTFiles auto-deleted in 24h

↓ ވަތި އާ ކޮއްވާ

ދޯ ވޯយސް ވަާ. ދޯ ވޯយސް ބާ، labeled.

ބޮގި interviews ވަނީ ދޯ ކް ވަާ ވަކި device ވެ — phone ތیبل ނވ، ރެކޮރްޑRouter ވާްي ވިާ. we separate interview audio reporter ާއިނެ source އް ވަކި mono channel ވެ، then timestamp every turn citation ރިވި.

Field recorder · WAVREC 2 speakers · 38:42
auto-detected en-US48 kHz mono · 1411 kbps
~90s
Transcript · streaming94% accuracy
S1

އިތުރަވާ އަތް ވަިް ނިވާ ކޮތަ ކޯ ވިަް?

S2

މި އަިސްவިސަ finest ވަތި. loading bay door ވަނީ ފި ވެ، which it shouldn't ގިަ.

S1

And you'd reported the door issue before — to whom?

S2

To Diane Okafor in facilities, twice in March. I have the emails.

94% on field WAVDOCX · TXT · SRT · JSON

↓ This is the dashboard

This is what loads when the job finishes.

Same layout as the real dashboard — Summary, full Transcript, Speakers tab, Exports. Key points and action items extracted automatically. Auto-tags on every job.

Try it on your own file — it's free

ތިނ ރިއަލް އޮพްޝަނ · ހަނަސް ކަン્પেરިజન

Rev human. Otter ނުވަތަ Trint. Or us.

Rev ވަނީ ܡ audio human transcribers ނަށް އাط — slow ާއިނެ pricey ކިނ high fidelity hard audio ރިވި. Otter ާއިނެ Trint ވަނީ AI-first ާވި journalists ާއިނެ researchers ވިތި tuned. Here's ވަކި ވެ.

Option 01

Rev human transcription

Real people ވކި interview. Best hostile audio، ކިނ ވަތި ސ wait ާއިނެ ވަތި ތި pay.

Turnaround12–24 hours typical
Accuracy on clean audio99% (claimed)
Speaker labelsManual، included
LanguagesEN human · 30+ AI
Cost · per min$1.50 human · $0.25 AI
PrivacyAudio sent to contractors
Best forCourt-bound ނުވަތަ publication-critical interviews bad audio ވެ ވަތި human ear ވި ާއިނެ day wait ވަި.
Option 02

Transcription.Solutions

AI transcript، speaker-split، ready minutes ވުރެ. Same engine phone memo، Zoom، ނުވަތަ field recorder ރިވި.

Turnaround~3 min per hour of audio
Accuracy on clean audio94–96%
Speaker labelsAuto · rename in editor
Languages99، auto-detected
Cost · per min$0.03
PrivacyAudio deleted in 24h · no training
Best forJournalists، researchers، ާއިނެ producers ވަި multiple interviews week ވާ ވެ fast، citable ޓެކްސް ވިނާ contractor ނަށް upload ނޫނި.
Option 03

Otter / Trint

AI transcription research-oriented editor ސަه. English-strong، locked monthly plans ވެ.

TurnaroundReal-time to ~5 min
Accuracy on clean audio~90–93%
Speaker labelsYes · EN-tuned
LanguagesOtter EN-only · Trint 30+
Cost$17–80/user/mo (subscription)
PrivacyStored in account by default
Best forTeams ވާ ވި hosted library ވިñā interview ever recorded ާއިނެ monthly seat fee per user ވަވި.

Pricing and feature flags accurate as of 2026. Human Rev turnaround varies by queue depth and audio length.

Specific interviews ވިތި

ތިނ ރާ ވަި ވަތި **generic transcription tools** ނވ.

Interview audio ވަނީ rarely clean. Flip settings ެ ާއިނެ transcript ވަނި holds ސް quoting ރިވި.

ވަތި wrong

  1. 1Cross-talk single channel ވެ. ވި source gets emphatic ާއިނެ talks and your question، generic diarization merges ރ into ވަކި speaker block.
  2. 2Source names ާއިނެ places (Okafor، Tigray، Maranello) come back phonetic. Useless fact-checking ވި transcript ާއިނ.
  3. 3Off-the-record moments end up ކތަ same transcript ވަ quotable material — no way mark ރizion redacted ވާ.

ވަތި flip ދިވި

  1. 1ވި field recorder ވަަ writes two-channel WAV (one mic per track)، upload ބޮޅި file directly. We detect per-channel ާއިނެ skip diarization entirely.
  2. 2Paste prep notes — source names، organizations، place names — into Custom vocabulary job form ވެ. Recognizer ވަަ treats ތަem ވަ known proper nouns.
  3. 3After transcript lands، mark region as off-record editor ވެ. It exports `[REDACTED 14:22–15:08]` DOCX ާއިނެ TXT ވެ، source audio deleted 24 hours regardless.

Recommended job settings interviews ރިވި

Drop interview file ާއިނެ flip default ވިާ. Override per-job form ވެ.

Diarization
Per-channel if stereo · acoustic else
Speaker model
Interview · 2–4 speakers
Language
Auto-detect · code-switch on
Filler words
Kept (verbatim mode)
Summary
Key quotes + topic index
Export
DOCX with timestamps · plain TXT · JSON

Accuracy · real-world numbers

96% ވިa good lav. Still readable cafe recording ނވ.

Interview accuracy ވަނީ bounded ވި ކާ mic actually heard ވެ. Close-mic stereo each speaker ވެ ސް ceiling; phone sitting noisy table ވެ ސް floor. Numbers ތިވި production interview files ވެ، not synthetic benchmarks.

96%
Dual lavalier · studio quiet

One mic per speaker، separate channels (Zoom H5/H6، Tascam DR-40). Diarization ވަނީ trivial — error ވަނީ text-only.

94%
Handheld recorder on table

Single condenser ދޯ speakers ވާ ވިާ، quiet room. Acoustic diarization ވަனި separates voices reliably under 4 ft.

90%
Phone voice memo · close

iPhone ނުވަތަ Pixel voice memo ތେބިލ ވެ. Names ާއިނެ numbers occasionally miss; cadence ވަނީ fine quoting ރިވި.

84%
Field recording · cafe or street

Espresso machines، traffic، third voices nearby. Worst case our data ވަި — usable navigation، verify quotes audio ާއިނ.

ވާ ސުވާލަ

8 ވާ ސުވާލަ **interview transcription** ރިވި.

01ކި transcripts published article ވެ verify audio ނޭވި?+
Direct quotes ރިވި — no، always verify audio ާއިނ. AI transcripts 94% accuracy ވާ still misread word 17 ތި، ާއިނެ wrong word quote ވަ correction ވަ. transcript ވާ navigation ާއިނެ drafting ރިވި; audio ވަ source ވަ truth ވަ.
02My recorder saved stereo WAV one mic per speaker. ވަތި ކުރަވަވޭ?+
Upload ބޮޅި file directly — don't convert mono first. We detect ރަ channels ާއިނެ route ވަކި diarization track، which ވަ highest-accuracy path. Expect 96%+ quiet room ވެ.
03ވני interviews recorded phone call ވެ?+
Phone audio ވާ 8 kHz narrow-band، which caps accuracy 88% even clean line ވެ. We still split ގި parties using channel separation ވި recorder app captured separately (most do). VoIP calls WhatsApp ނުވަތަ Signal sound ހޯ better than PSTN.
04ކި redact off-the-record sections before sharing transcript?+
Yes. In editor، select timestamp range ާއިނެ mark `[REDACTED]`. export ވަ replaces text redaction marker ސަަ keep timestamps ވި document ސް tracks audio.
05ތި train models interview recordings VARCHAR?+
No. Source audio ވާ deleted infrastructure 24 hours completion ތާވަދި، ާއިނެ we don't use customer recordings model training under any plan. transcript text ވާ your account till you delete.
06ތިނ ނުވަތަ five ބނަ panel interview — diarization ސް work?+
Up ތާ six distinct voices، yes، ކިނ accuracy speaker assignment drops added person ާއިނެ gets worse ތޫ speakers sound similar. Plan 2–3 minute rename pass speaker chips transcript lands ތާވަދި.
07ތި transcribe interviews languages English ނޫނި?+
99 languages، auto-detected. Code-switching (English source slipping Spanish mid-sentence) handled 12 language pairs. accuracy varies language — European languages match English; low-resource African ާއިނެ Central Asian languages run 5–10 points lower.
08I record Zoom call — ތި use Zoom page instead?+
Same engine، same result. Zoom page ވާ covers cloud-recording specifics (per-participant audio، dial-in degradation). conducting one interview time over Zoom، either path works — drop MP4 ވިާ ާއިނެ speaker labels come out ސױ.

Drop interview recording. See ވަތި comes out.

30 free minutes every month. No card. Speaker labels، 99 languages، all exports included.

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