Ukuguqulelwa kweqembu lokuloba — guqulelela irekhodhi yeqembu lokuloba ngebhezi lomuntu ngamunye

Ukuguqulelwa kweqembu lokuloba.Umuntu ngamunye onebhezi, ilizwi lonke.

Lahla irekhodhi yeqembu lokuloba elinabhasela, 8, kanye nezi 10 izwi. Thola umbala wokuguqulelwa ethuliswe enomuntu ngamunye obekhozo, umkela othunjile onekhoziwe, kanye ne-DOCX efuna u-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

Abantu abayisishiyagalombili kusisindo. Onebhezi ethuliswe kusisindo.

Amaqembu okuloba ayizimo ezinkingizane kakhulu kukulwazi kwethu — izisabisabi ezilingana, izwi elilingana, umkela othunjile wenobanzi ohinyela. Sithubela umkela othunjile kungisinye kunekusikhutshe, bese uguqula Esikhali 3 → 'Participant_F2' kanye nokh oyisiphumulelela.

Irekhodhi yeqembu lokulobaREC Umholi + abantu abayisishiyagalombili · 1:23:14

i-en-US eyaziwa ngoukuzenzekelela44 kHz boundary mic · WAV

~90s

Umbala wokuguqulelwa · ukuvela ngayoUkunemba okungaz i 91% · abantu abayisishiyagalombili abakhuluma

Ngakho lapho uqale ukuvula umweli — ngitshele ngokucacile ukuthi wazi yini.

Kubona? Into yokuqala kwakuyingi. Njengesibhedlela, okwenza ngokunthuthuka —

Yebo, okuyinfano nami. Ngacabanga ukuthi kwakumele ube i-lavender enye.

Kwey, futhi ulebheli luthi lavender kodwa aktubi —

Ukunemba okungazi 91% komuntu abayisishiyagalombili nge-room micDOCX (ikunziselezeni i-QDA) · 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

Umuntu ka-Rev. I-AI ekunyameni. Noma thina.

Abacwaninga abakhetha kahle phakathi kokukhokha umuntu owokuguqulelwa (konakele, kunembile, kukhawuleza) noma ukuthumela wumfayili ngaphansi kwe-AI elijwayelekile elihlukumezekile amaqembu enabhasela ayisishiyagalombili. Sitshala phakati — isivinini se-AI, kukhusela amaqembu okutholwa kweqhoqo, kanye ne-DOCX eyakha u-NVivo ngaphandle kwemsebenziso.

Option 01

Umuntu ka-Rev owethuliswe

Umuntu abaletshela. Ukunemba okukhulu, kodwa ukubuyiswa ngezinsimu 12-24 kanye nentengo eyakha ngekhola.

Ukunemba~99% (umuntu)

Ukubuyiswa12–24 izinsimu eziqhelekile

Umkela othunjileKubekhozo [umkela othunjile]

I-QDA exportI-DOCX, iqhuba-qhuba yokulungiselela

Intengo · nge-ilizwi$1.50 ethuliswe

Iqembu elingu-90min~$135

Best forUmsebenzi wocwaningo noma ucwaningo olukhonziwe lapho zonke izinto ezingawugculiswa kumelwe ukuvunyelwa umuntu.

Option 02

Transcription.Solutions

Ukukhusela amaqembu okubhalela amabhasela enangaz i 6-10, umkela othunjile obekhozo kungisinye, i-DOCX export esigweshwe i-NVivo, ATLAS.ti, kanye ne-Dedoose.

Ukunemba88–94% kumusicala wegabu

Ukubuyiswa~1× izikhathi zomuntu

Umkela othunjileObekhozo, akusuwe

I-QDA exportI-DOCX enabhasela okhulumayo

Intengo · nge-ilizwi$0.03

Iqembu elingu-90min~$2.70

Best forAbacwaninga abamjaza amaqembu amambalwa abudingela umbala wokuqala u-NVivo nge-ngomuso ekuseni, hhayi ngaphakameni.

Option 03

I-Otter / Sonix

I-AI ejwayelekile etenjiwe konvocals. Okuhle kunabhasela abangababili-bathathu, ibhubheka kunabhasela abahlanu — futhi exports awanqumbi i-QDA software.

UkunembaKungenela kunabhasela abahlanu

UkubuyiswaKukhawuleza

Umkela othunjileUsuwe kafushane

I-QDA exportAyikho i-NVivo format esilungile

Isibalo se-speakerIsethulo ~6

Intengo$17–22/umsebenzisi/inyanga

Best forIzinkulumo ezincane kanye ne-1-on-1s lapho irekhodhi inabhasela abangababili-bathathu futhi ihlala ku-calendar workflow.

Intengo enembile ngo-Meyi 2026. Izikhundla zokunemba zivela kusampula sethu samaphakamani esishni, akekho ocwaningo olungenelela.

94% ehusayo-ngomusu nomuntu ngamunye. Ima ku-82% kumicala umuntu owodwa.

Ukunemba kweqembu lokuloba kukhulekelwa yindlela ye-microphone, hhayi imodeli. Ilavalier kumuntu ngamunye kuninika iziqephu zalutho ozamile — ukulwa nokulwa kuvela nengubane. Umicale umuntu owodwa etafuleni lesithombe enomunye abantu abayisishiyagalombili abakhuluma yilula le nkinga. Izinombolo zingezansi zivela kuamarekhodi okucwaninga okuskandiswe kumaphaneli akho.

Izinto eziyisishiyagalombili abantu abayo imibuzo ngokuguqulelwa kweqembu lokuloba.

01Ngingaguqula i-Speaker 1 kugameni lokucoca lomuntu noma i-ID?+

Yebo. Chofoza indawo enye ye-speaker kumhleli, thayipela igama noma i-screener ID (nge-P04_F_34), futhi iyopela kuma-turn onke kumuntu oshiye embhaleni. I-DOCX export isebenzisa amabhezi akhethwe ngabomu.

02Uzihlekelela kanjani umkela othunjile nokukhanqa komuntu okuthunjile?+

Sithubelela kungisinye nge-`[umkela]` izibopho nokugcina umuntu womuntu umbala. Imithetho ejwayelekile ngokuvamile ikhetha umuntu owodwa nokubeka okunye — makuwemule, ngoba izikhundo zokuthunjile zingazimbali lapho izinambathiselo zeqembu lokuloba ziphakama.

03Ngubani i-DOCX iyakhupha nokulandelela nge-NVivo kanye ne-ATLAS.ti?+

Yebo. Sisikhiye enebhezi esikhali njengesikhonzo sesitayela, i-NVivo i-auto-code ngenso kanye ne-ATLAS.ti ayikho amathuluzi abakhuluma. I-Dedoose yamukela i-DOCX efanayo nendlela ye-transcript yokufaka.

04Ubani abantu abavakala abalingana ku-file yenye?+

Isikhala escindezeleka mazilingani 12. Ngaphandle kwalokho, ukulwa nokwazi kuqala kukahlanganyela izwi elifanele — okusho ukuthi 10-15 izinsimu zokuguqula nge-side yakho. Setha 'Abantu abalindelekile' ngokucacile kumfanekiso wosebenziso kwezinye izinambathiselo.

05Ethuliswe noma ilungiselwe — ngingakhethwa?+

Kokubili. Indlela ethuliswe igcina yonke 'um', ukuqala okuxakayo, kanye nelizwi eliphindwe ngalunye lokwakhela engubane. Ilungiselwe isusa ibandlule lokuhlanganisa. Ukhethela nge-job; okuzenzekela okuthuthako ye-template yocwaningo kuwethuliswe.

06Yini ngokuthathelwa kwamakhono kanye nokuvikela inhlonipho yabadalulwe?+

Amafayela alandelwa ku-infrastructure yakho, ayasiwe i-APIs yomnumzane wethathu. Sinikeleza i-per-job i-auto-delete-after-N-days flag kwa-IRB protocols. Singu-SOC 2 Type II futhi i-GDPR; i-DPA iphansi kwepheji yobufundi uma i-IRB yakho idinga yona.

07Ngingakwenza ividiyo noma sesizwi kuphela?+

I-sesizwi kuphela kwiqiniso — asingasebenzisi ividiyo kukulwa nokwazi. Uma une-video yokunqumlela abadalulwe, igcinele umuntu wakho wokuhlobo; faka isigabu sesizwi kuphela kukhawuleza kanye nokukha isikhatimane.

08Intengo iveza kanjani i-Rev human verbatim?+

Iqembu elingu-90-minute lidumele ~$2.70 kodwa ngenani ~$135 ku-Rev verbatim. Ukuguqula kuwukunemba: sithawathe ku-86-94% okuxhomilekile ku-mic setup, i-Rev hithhisayo zomuntu bazithule ~99%. Abacwaninga abamimele usebenzisi wokuqala futhi abandukela umuntu um uma kudingekile.