Ntinyere mgbakọ ndị ọkọ — tinye mgbakọ ndị ọkọ jide onye ekwu maka onye ọbụla na-akọ onyinye

Ntinyere mgbakọ ndị ọkọ.Onye ekwu ọbụla akọtara, okwu ọbụla.

Tinye ifoto mgbakọ ndị ọkọ na 6, 8, karị ọbụ 10 olu. Nwụta akwụkwọ mkpiriti ozugbo na onye ọbụla akọtara, okwu na-agba ụdụ akọtara, na DOCX na-aba n'NVivo.

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

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

Onye asaa na-aba n'akaụ. Akọtara ozugbo pụtara.

Mgbakọ ndị ọkọ bụ ihe kasị ike n'ọrụ diarization — ndị a na-agụ otu ụzọ, ututu a dịkwa otu, okwu na-agba ụdụ na-eche mgbe niile. A na-akọ okwu na-agba ụdụ na-akọwa aka ha ọzọ ọ bụghị igbapụ ha, mgbe ahụ gbanwe Speaker 3 → 'Participant_F2' otu ugboro na o gaara n'okirikiri.

Ifoto mgbakọ ndị ọkọREC Onye njikọ + onye asaa · 1:23:14

akụkụ nke en-US44 kHz boundary mic · WAV

~90s

Akwụkwọ mkpiriti · na-agba91% na-eme nke ezi · onye 8

Ya, mgbe ị meghari ihe mkpuchi ahụ — akọwa m ihe i hụrụ.

N'eziokwu? Ihe mbụ bụ isi isi. Dika ụlọ ọgwụ, onyeozi —

Eeh, otu. Echere m na ọ ga-abụ nke lavender.

Nke mma, na akara ya sịrị lavender mana ọ gaghị nke bụ —

91% na onye 8-speaker room micDOCX (QDA-ready) · SRT · TXT · JSON

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.

app.transcription.solutions / interview-202.mp3Export

Summary 5Transcript 1,420Speakers 2Exports

interview-202.mp347:08128 kbps CBR2 speakersen-US auto-detected

Founders need post-call content, not just transcripts. Tools force them to stitch 5 apps together.

Sample preview from a founder interview about post-call workflow. Real transcripts look exactly like this — same tabs, same summary block, same key-points / action-items split, same auto-tag chips.

Key points

Gap exists between raw recordings and shippable content — tools stop at transcript.

Show notes, social clips, blog drafts all expected by call's end, not next-day.

Current tooling fragmented across 5 apps — no single pipeline.

Conversion-rate signal flipped a buyer-segment assumption at week 3.

40% of original hypothesis survived — the shape held, mechanics rebuilt.

Action items

Speaker 1Investigate single-pipeline approach to replace 5-app stitch.

Speaker 2Mock how show-notes draft could flow from the transcript.

Speaker 2Pull conversion-rate by segment, Monday EOD.

Speaker 1Map the 5-app stitch & list which steps actually need a human.

Auto-taggedfounder interviewpost-call contenttooling fragmentationsingle pipeline

Try it on your own file — it's free

Rev onye mmadụ. AI nkịtị. Maọbụ anyị.

Ndị ọmụmụ na-ahọpụta n'etiti inye onye ntinyere ego (nwayọ, nke ezi, ụtụ) maọbụ ịgba ihe ahụ site na ngwa AI nkịtị na-agụ ụzọ enweghị ụzọ maka olu 8. A nọ n'etiti — ngwa AI ọsọ, diarization lụrụ maka akwụkwọ ọmụmụ, na DOCX na-aba n'NVivo n'adịghị ehie.

Option 01

Rev onye mmadụ ozugbo

Onye mmadụ na-edebanye ya. Nke ezi nke ọma, mana oge 24 hours na ọnụ ọchị na-abawanye site n'oge.

Nke ezi~99% (onye mmadụ)

Oge nlọghachi12–24 oge a na-etụ

Okwu na-agba ụdụAkara [crosstalk]

Mgbasa QDADOCX, mgwakọta aka

Ọnụ ọchị · na nkeji$1.50 ozugbo

Mgbakọ nkeji 90~$135

Best forỌrụ gụ iwe maọbụ ọmụmụ na-ejide ịbụ na onye mmadụ na-enye aka maka onye ncha nke disfluency.

Option 02

Transcription.Solutions

Diarization lụrụ maka 6-10 olu, okwu na-agba ụdụ akọtara n'akọ, mgbasa DOCX nrụ maka NVivo, ATLAS.ti, na Dedoose.

Nke ezi88–94% na okwu mgbakọ

Oge nlọghachi~1× okwa oge

Otú okwu na-agba ụdụAkọtara, adịghị igbapụ

Mgbasa QDADOCX na onye ekwu na-atụnye

Ọnụ ọchị · na nkeji$0.03

Mgbakọ nkeji 90~$2.70

Best forNdị ọmụmụ na-agba mgbakọ ọtụ ọtụ na-achọ akwụkwọ mkpiriti mbụ n'NVivo n'echi, ọ bụghị mma ole.

Option 03

Otter / Sonix

AI nkịtị e mere maka mkpokọta. Ọzọ n'onye 2-3, na-atụpụ site na 5 — na mgbasa adịghị akpọ ngalaba ọrụ QDA.

Nke eziAdatawoghị site na onye 5

Oge nlọghachiỌsọ

Okwu na-agba ụdụNa-agbapụ ike

Mgbasa QDAEnweghị ụzọ NVivo

Iji onye kachaNchikọta nwayọ ~6

Ọnụ ọchị$17–22/onye/ọnwa

Best forMkpụrụ ihe kpọmkwem na 1-na-1 ebe ifoto nwere olu 2-3 na bi na ọrụ kālenda.

Ọnụ ọchị na-ezi ihe ka o dị May 2026. Anya ụzọ nke ezi si na sampụl n'ime aka anyị nke ihe mmadụ na mgbakọ ndị ọkọ, ọ bụghị benchmark ngwaahịa.

94% na lavalier-kwa-onye. Na-eme ike 82% na otu mic ụlọ.

Nke ezi mgbakọ ndị ọkọ na-agbadị site na topọlọji microphone, ọ bụghị ngwa. Lavalier na onye ọbụla na-enye anyị n'ọkụọkụ pụta kwa onye — diarization ghọrọ nke mfe. Otu mic ụlọ na mmechi tebụl na olu 8 bụ ile ihe siri ike. Ọnụ ọchị n'okpuru sitere na ndọc nmụ na pipeline anyị.

Ihe 8 ndị mmadụ na-ajụ maka ntinyere mgbakọ ndị ọkọ.

01A m enwe ike igbanwe Speaker 1 ka aha nke onye ọbụla maọbụ ID?+

Ee. Pịa akara onye ekwu ọbụla na editọ, dee aha maọbụ nkwadọ ID (dịka 'P04_F_34'), na o gaara nile na-atụnye nke onye a si n'akwụkwọ mkpiriti. Mgbasa DOCX na-eji akara a gbanwere.

02Kedu ka ị na-eme okwu na-agba ụdụ na okwu na-atụpụta?+

A na-akọ ya n'akọwa na `[overlap]` akara na-akọ onye ekwu abụọ ihe ha kwuru n'akwụkwọ mkpiriti. Ngwa nkịtị na-ahọpụta olu otu na-agbapụ nke ọzọ — a na-agbaghị, n'ihi na nkeji overlap bụ ebe nsonaazụ mgbakọ ndị ọkọ na-ebi.

03A DOCX a na-ewepu azụ na NVivo na ATLAS.ti n'ụzọ dị nma?+

Ee. A na-ewepu na akara onye ekwu dịka ustedi paragraf ugbu, na NVivo na-agba ike n'oge mbanye na ATLAS.ti na-amaghị dịka okwu na-atụnye. Dedoose na-tanụ DOCX nkịtị site na ụzọ mbanye mkpiriti.

04Ole onye ekwu ka ị nwere ike diarize na ihe otu?+

Nchikọta nwayọ gburugburu 12. Karị nke, ngwaahịa ike anụmanụ na-amalite igbipụ olu ndị nchịkọta — ya na-apụta nkeji 10-15 na-eyi na gbanwe onye chip n'ọtụtụ nke. Tụọ 'Expected speakers' n'ụzọ ọrụ maka ihe ndị kacha mma.

05Ozugbo maọbụ emeghe — a m nwere ike ịhọrọ?+

Ehee. Ngwa okwu ozugbo na-akọ nke ọbụla 'um', meghe mmalite, na okwu ruru ọtụtụ maka nyocha olu. Meghe na-ewepụ disfluencies maka agụ aka. Ị na-ahọrọ na-otu ọrụ; ịbụ maka template ọmụmụ bụ ozugbo.

06Gini maka IRB nkwadọ na ihe nkwadọ onye?+

Ihe na-agba site na nchekwa anyị, ọ dịghị n'API API ndị ọzọ. A na-enye kwa-ọrụ auto-delete-after-N-days akara maka protokọl IRB. A bụ SOC 2 Type II na GDPR-na-eme; DPA nọ na peeji ọkwa ọrụ ma IRB gị na-achọ.

07A m ga-ebe vidio maọbụ olu naanị?+

Olu naanị dịba — a na-ejikọ vidio maka diarization. Ma ọ bụrụ na ị nwere vidio maka akụkọ onye, jide ya n'ebe ọ bụ maka anụma gị nke odide; itinye track olu naanị na ọsọ ma rụ ego.

08Kedu ka ọnụ ọchị na-atụ Rev onye mmadụ ozugbo?+

Mgbakọ nkeji 90-chere gbasara $2.70 ebe a karị ~ $135 na Rev ozugbo. Ịgbagha bụ nke ezi: a na-ede 86-94% dabere na ihe muo, onye mmadụ Rev na-ede ~99%. Ọtụtụ ndị ọmụmụ na-eji anyị maka mbụ na-adị naanị gbasaa mgbakọ nkụ na-ama mmadụ ma a chọ.