Àwọn Àkọlé àwòrán

Automatically identify and label different speakers in your audio and video transcriptions. Know exactly who said what.

Àwọn iṣẹ́ láti mú àwọn àwòrán àti àwòrán tí a yàn fún gbogbo eniyan. Àwọn àwọn ìròyìn tí a dáwọ́ láti lo DRM kò fọwọ́sì.

Àwọn ìṣàfihàn fún àwọn ìṣàfihàn

Private transcript

Fi àkọlé pamọ́

Ṣí àwọn àwọn àgbéwọlé →

Tí fáìlì náà síbẹ̀ tàbí tẹ̀ láti ṣàfihàn

MP3, WAV, M4A, FLAC, MP4, MKV, MOV, WebM — to 2GB

Fi àwọn fáìlì mìíràn pamọ́ Àwọn àwọn àwọn àwọn àwọn

Àwọn ìṣàfihàn fún àwọn ìṣàfihàn

Private transcript

Fi àkọlé pamọ́

Ṣí àwọn àwọn àgbéwọlé →

Àwọn ìṣàfihàn fún àwọn ìṣàfihàn

Àwọn àkọlé àìpẹ́ láti inú àkọlé. AI kọ̀ọ̀kan-ìṣàmúlò-ètò bí a tí n sọ̀rọ̀ - ìṣàmúlò-ètò náà tí a bá kọ̀ọ̀kan àwọn àkọlé náà.

Àwọn àwọn àmì-ìwé

10 free min/day 600 min ọfẹ pẹlu iforukọsilẹ Kò ní kaadí ẹ̀yàn Àwọn àmì-ìwé

Ṣẹ̀dà nípa ọ̀fẹ̀ →

Kini Ìṣàfilọ́lẹ̀ Àwọn Àkọlé?

Speaker diarization is the process of partitioning an audio stream into segments according to the identity of the speaker. In simpler terms, it answers the question "who spoke when?" This is essential for multi-speaker recordings like meetings, interviews, podcasts, conference calls, and legal proceedings where knowing who said what is just as important as what was said.

STT.ai uses advanced neural speaker diarization models that can detect and label speakers in real time. The system creates speaker embeddings -- numerical representations of each voice's unique characteristics -- and clusters them to distinguish between different people. This works even when speakers have similar voices or frequently interrupt each other.

Bií a ṣe lè Lórí Ìṣàfilọ́lẹ̀ Àwọn Àkọlé

1. Àwọn Ìṣàfilọ́lẹ̀ Àwọn Ààyè-iṣẹ́ Àwọn Àmì-ìwé

Iṣẹ́ naà ní a tì sọ̀rọ̀ pé, ìdí nípa ohun tí a ǹṣè nípa ìgbésẹ́, ìgbésẹ́, àti ìgbésẹ́.

2. Ìṣàfilọ́lẹ̀ Àwọn Àkọlé

Each speech segment is converted into a speaker embedding -- a compact vector that captures the unique vocal characteristics of the speaker.

Àwọn àmì-ìwé

Àwọn ìṣàfilọ́lẹ̀ ní pàtó láti fi àwọn ààyè kọ̀ǹpútà pọ̀ ní pàtó láti inú olugbálẹ̀ẹ̀lì kan, láti inú ààyè kan ní pàtó àmì-àṣírí (Olugbálẹ̀lì 1, Olugbálẹ̀lì 2, abbl.).

Àwọn Ìṣàmúlò-ètò Fún Àwọn Àkọlé

Àwọn Àkọ́kọ́ Àwọn Àgbègbè

Automatically label each participant in meeting recordings. Generate minutes with clear attribution of who said what.

Àwọn àkọlé

Fi àwọn ààyè-iṣẹ́ àti àwọn awáròyìn pamọ́ sípapọ́tì. Ṣẹ̀dà àwọn àmì-ìwé ìṣàfihàn láti fi àwọn àkọlé àwọn ìṣàfihàn àwọn ìṣàfihàn àwọn ìṣàfihàn àwọn ìṣàfihàn àwọn ìṣàfihàn.

Àwọn Àkọ́kọ́

Ṣayẹwo awọn ibaraẹnisọrọ ati awọn ibaraẹnisọrọ fun awọn iwadii, awọn iroyin, ati awọn iwe-aṣẹ ifowopamọ.

Àwọn Àwọn Àṣẹ

Create official records of depositions, hearings, and compliance calls with clear speaker identification.

Speaker Detection on STT.ai

Speaker detection is available on all paid plans. When you transcribe audio or video with speaker detection enabled, the transcript will include speaker labels inline with the text. You can also export speaker-labeled transcripts in all supported formats including SRT, VTT, DOCX, JSON, and PDF.

Speaker 1 [00:00:01]: Welcome to the meeting, everyone. Let's start with the quarterly review. Speaker 2 [00:00:05]: Thanks. I have the numbers ready. Revenue is up 23% quarter over quarter. Speaker 1 [00:00:12]: That's great news. Can you walk us through the breakdown?

The system can detect up to 20 distinct speakers in a single recording. For best results, ensure each speaker has at least a few seconds of solo speech. Overlapping speech is handled but may reduce accuracy in heavily cross-talked segments.

Wá àwọn ààyè-iṣẹ́ ìṣàfihàn ní bayii

Upload a multi-speaker recording and see speakers automatically labeled.

Ṣí Ìṣàfilọ́lẹ̀

Àwọn Àtòjọ-ẹ̀yàn

speaker detection runs in your browser: paste a URL, upload a file, or record from your mic. STT.ai picks the AI model and returns the transcript in under 5 minutes. Export as TXT, SRT, VTT, DOCX, JSON, or PDF.

Yes — every visitor gets 600 free minutes/month on STT.ai, usable for speaker detection the same as any other workflow. Paid plans starting at $5/month unlock longer files, private transcripts, and priority queueing.

speaker detection runs on the same AI models as the rest of STT.ai — our best models reach 95-97% accuracy on clean speech (3-5% Word Error Rate on benchmarks). Switch models on the fly if the first pass is below your target.

speaker detection can run on any of STT.ai's 10+ models — STT.ai Enhanced (most accurate), Whisper Large V3 (99 languages), NVIDIA Canary (#1 WER on supported langs), Whisper Turbo (fast), Moonshine (lightweight), and more.

Yes. Every transcript exports as SRT or VTT — works with YouTube, Vimeo, TikTok, VLC, and every major video player. The burn-subtitles tool overlays them onto video as hardsubs.

Yes. Speaker diarization automatically labels each voice (Speaker 1, Speaker 2, ...) and you can rename them in the built-in editor. Works across all models and languages.

Most speaker detection jobs finish in under 5 minutes. A 1-hour audio file typically completes in 2-3 minutes with our fastest models. Speed depends on chosen model and current GPU load.

speaker detection accepts 20+ formats — MP3, WAV, M4A, FLAC, OGG, MP4, MKV, MOV, WebM, AVI, and more. Output to TXT, SRT, VTT, DOCX, JSON, or PDF.

Yes. Audio files submitted to speaker detection are processed and deleted by default. Pro plans add client-side encryption — even if STT.ai's database is breached, your transcripts are unreadable without your key. Data is never used for model training without explicit opt-in.

Yes. STT.ai offers a REST API with Python and Node.js SDKs, plus an MCP server for Claude and Cursor — all usable for speaker detection workflows. Free API tier includes 100 minutes/month.

Yes. Every transcript opens in the built-in editor where you can correct words, rename speakers, adjust timestamps, and add notes. All changes save automatically.

Every transcript gets a unique shareable URL. Export to DOCX or PDF for email. Pro plans add password-protected and permanent links — useful for client work.

STT.ai handles 1,300+ platforms including YouTube, Vimeo, TikTok, SoundCloud, Zoom, Google Meet, podcast hosts, and more. URL transcription works with publicly-available content only — DRM-protected sources can't be transcribed.

Àwọn Àkọlé àwòrán

Kini Ìṣàfilọ́lẹ̀ Àwọn Àkọlé?

Bií a ṣe lè Lórí Ìṣàfilọ́lẹ̀ Àwọn Àkọlé

1. Àwọn Ìṣàfilọ́lẹ̀ Àwọn Ààyè-iṣẹ́ Àwọn Àmì-ìwé

2. Ìṣàfilọ́lẹ̀ Àwọn Àkọlé

Àwọn àmì-ìwé

Àwọn Ìṣàmúlò-ètò Fún Àwọn Àkọlé

Speaker Detection on STT.ai

Wá àwọn ààyè-iṣẹ́ ìṣàfihàn ní bayii

Àwọn Àtòjọ-ẹ̀yàn

How does speaker detection work on STT.ai?

Is speaker detection free?

How accurate is speaker detection?

What AI models can I use for speaker detection?

Can I get subtitles from speaker detection?

Does speaker detection detect different speakers?

How long does speaker detection take?

What input formats does speaker detection support?

Is my audio private when I use speaker detection?

Is there a speaker detection API?

Can I edit a speaker detection transcript after?

How do I share what speaker detection produces?

What other platforms work beyond speaker detection?