Túmọ̀ MP3 sí ọ̀rọ̀, kíá · transcription.solutions

Túmọ̀ MP3 sí ọ̀rọ̀.Àmì àgbésòrọ̀, àwọn èdè 100 jùlọ.

Júlọ́ eyikẹ́ MP3 — àkọ́sílẹ̀ ohun 32 kbps ti a tẹ̀ sílẹ̀ tàbí ìpele 320 kbps — kí o sí gba àkọ́sílẹ̀ pẹ̀lú àmì àgò àti àmì àgbésòrọ̀ láàárin ìsẹ́jú 90.

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

Audio in. Transcript out.

Drop a file, paste a URL, or record live — text appears back with speaker labels and timestamps. Same pipeline whether the source is a file, a URL, or your microphone.

Microphone · liveREC 00:07.41

en-US auto-detected16 kHz mono

~90s

Transcript · streaming2 speakers · 47:08

Thanks for making the time. I want to start with framing — what was the original hypothesis behind the project?

Honestly, maybe forty percent. The shape held — the mechanics underneath had to be rebuilt almost entirely.

What flipped it for you? Was there one customer call, one piece of data

~95% accuracy on clean audioSRT · DOCX · 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

Option 01

Built-in dictation

Live, free, on-device. Handy for short bursts while you talk.

Accuracy · clear English~85%

Speaker separationNo

TimestampsNo

Languages~30

60-min fileLive only

CostFree

Best forShort voice notes while you walk. Hands-free messaging. Dictating an email at a stoplight.

Option 02

AI speech-to-text

~30× faster than realtime. 100+ languages. Speaker labels. The sweet spot for most work.

Accuracy · clear English95%+

Speaker separationYes (Pro+)

TimestampsPer sentence

Languages100+ auto

60-min file~90 s

Cost · per min$0.03

Best forInterview recordings · meeting notes · podcast transcripts · YouTube subtitles · batch jobs · API automation · field journalism.

Option 03

Human transcriber

Gold-standard accuracy when the audio is hard or the stakes are legal.

Accuracy · clear English98–99%

Speaker separationManual

TimestampsPer turn

LanguagesPer transcriber

60-min file4–8 hours

Cost · per min$1–3

Best forLegal depositions · medical dictation · archival oral history · anything where 95%+ accuracy is non-negotiable.

Built-in dictation figures from public iOS / Android speech API benchmarks. Human transcriber rates from US/UK industry surveys 2024–2025.

6 things people ask about this.

01Àwọn ìwọ̀n bitrate MP3 wo ni a ṣètìlèyìn?+

Gbogbo ìwọ̀n bitrate MP3 déédé láti 32 kbps dé 320 kbps, mejeeji CBR (ìwọ̀n tí ó dùró) àti VBR (ìwọ̀n tí ń yipadà). Déédé dára jùlọ ni 128 kbps àti lókè. Nísàlẹ̀ 64 kbps, ìtẹ̀tẹ́ ń bẹ̀rẹ̀ sí nípa lórí déédé ọ̀rọ̀ — pètò àyẹ̀wò àtòwọ́tọ́ fún àwọn ìgbàsílẹ̀ ni ìpele yìí.

02Ṣé yíyí MP3 mi si WAV níṣàájú ń mú déédé pọ̀?+

Rárá. Yíyí MP3 si WAV kò gbà ọ̀rọ̀ tí ó pàdànú láti ìkoodu MP3 padà. Tí o bá ni ìgbàsílẹ̀ àtíjọ́ ni WAV tàbí ìrí láìpàdànú, lò èyí tààrà fún àbájáde tí ó dára díẹ̀. Ṣùgbọ́n MP3 déédé ni 128 kbps+ jẹ́ ohun ìkóhun tí ó dára lórí ara rẹ̀.

03Kí ni ìwọ̀n fáìlì MP3 tí ó pógbón jù?+

Free: 100 MB àti tó 30 ìsẹ́jú fún fáìlì kan (eyikẹ́ tí ó bá kọ́kọ́ dé). Pro: 2 GB àti tó 10 wákàti fún fáìlì kan (nínú 8–9 wákàti ni 128 kbps). Business: 5 GB àti tó 10 wákàti fún fáìlì kan. Fún àwọn àkójọ fáìlì púpọ̀, fi fáìlì kọ̀ọ̀kan sílẹ̀ gẹ́gẹ́ bí iṣẹ́ API yàtọ̀ — Pro ń ṣiṣẹ́ tó 20 iṣẹ́ ní ìgbà kan, Business tó 50.

04Ṣé mo lè gba fáìlì SRT láti MP3 kan?+

Bẹ́ẹ̀ni. Kó SRT tàbí VTT jáde tààrà láti ojúewé àkọ́sílẹ̀ — ó wulò fún gbígbé àkọ́sílẹ̀ padà sí YouTube, fídíò ìṣàtúnṣe, tàbí àkọ́sílẹ̀ pẹ̀lú àgò. Àwọn àmì àgò ń bá àwọn ipò fáìlì MP3 àtíjọ́ mu.

05Báwo ni ó ṣe ń fi ìgbà tó láti túmọ̀ MP3?+

Fáìlì MP3 60-ìsẹ́jú ń parí iṣẹ́ ní 60–120 ìsẹ́jú. Àwọn fáìlì gígùn ń pín sí àwọn èkà tí wọn ń ṣiṣẹ́ ní ìgbà kan — fáìlì 4-wákàti kò gba ìlọpò 4 ní ìgbà. Àwọn fáìlì Business ń gba ìṣájú ìṣiṣẹ́.

06Ṣé ó ń ṣiṣẹ́ fún àwọn MP3 tí kì í ṣe Gẹ̀ẹ́sì?+

Bẹ́ẹ̀ni — àwọn èdè 100 jùlọ, ti a ṣèwárí ládáa láti àwọn ìsẹ́jú 30 àkọ́kọ́ tí ohun. Àwọn èdè Ìpele 1 (Gẹ̀ẹ́sì, Sípáníìṣì, Jẹ́mánì, Faransé, Pọrtugíìsì, Ítálì, Dọ́ọ̀lù, Póláǹdì) ń pese 95%+ déédé lórí bitrate MP3 déédé. Ìpele 2 (Rọ́ṣíà, Jàpáànù, Mandarin, Kóréà, àti 13 mìíràn) ń pese déédé ìpele ìṣẹ́.