Ku- hadlaha Ogaanshaha & Diarization

Si otomaatig ah u aqoonso oo ku calaamadee kuwa hadlaya ee maqalka iyo fiidiyowga. Ogow cidda wax tiri.

Shaqada la audio iyo video dadweynaha la heli karo. DRM-daboolka content ma taageersana.

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Kordhinta loogu talagalay Enhanced
Private transcript
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Kordhinta loogu talagalay Enhanced
Soo qaadista: 0:00
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Maxaa Speaker Diarization?

Speaker diarization waa habka qaybinta audio stream in qaybaha sida ku cad aqoonsiga afhayeenka. In ereyga fudud, waxay ka jawaabtaa su'aasha "oo ku hadlayo marka?" 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.

Sida ay u shaqeyso aqoonsiga hadalka

1. Voice Shaqooyinka Ogolaansho

nidaamka ugu horeysay aqoonsan waxa qaybaha audio ku jira hadalka ka dhanka ah quus, muusig, ama codka background.

2. Afhayeenka Embedding

Qayb kasta oo hadal ah waxaa loo beddelaa mid ku dhejinaya afhayeenka - vector compact ah oo soo bandhigta astaamaha codka ee gaarka ah ee afhayeenka.

3. Clustering & calaamadeynta

Embeddings waa clustered in qaybaha koox ka hadlaya isku mid ah oo isku mid ah, ka dibna cluster kasta waxaa loo magacaabay label (Speech 1, Speaker 2, iwm).

isticmaal kiisas loogu talagalay Speaker Detection

Qoraalka Kulanka
Automatic label ka qaybgalaha kasta oo kulan diiwaangelinta. abuuro daqiiqado la sharaxaad cad oo ku saabsan cidda ay yidhaahdeen waxa.
Podcast-ka
Kala sooc dhexdooda martida iyo martida podcast episodes. abuuro muujiyaan qoraalada la hadalka saxda ah.
Wareegto
kala sooc su'aalaha iyo jawaabaha su'aalaha u cilmi, warbaahinta, iyo diiwaangelinta shaqaalaha.
Sharciga iyo waafaqsanaanta
abuuro diiwaanada rasmiga ah ee depositions, dacwadaha, iyo wacadaha waafaqsan la aqoonsiga qaylo-dhaan cad.

Ku-hadalka Ogolaanshaha 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.

Ka fikir aqoonsiga hadalka hadda

Soo deji multi-hoosaadka diiwaangelinta iyo arko hadalka si otomaatig ah loo calaamadeeyay.

Bilow ku qoro bilaash ah

Su'aalaha badanaa la isweydiiyo

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.