Penemuan Speaker & Diarization

Ngaidentipikasi sarta ngalabelkeun pangucap anu béda sacara otomatis dina transkripsi audio jeung video anjeun. Terang persis saha anu nyarios naon.

Ngagunakeun audio & video anu aya di dieu. Kandungan anu dilindungi ku DRM henteu didukung.

Ningkatake kanggo Diperbaiki
Private transcript
Chat with transcript
Buka karo Pro →
Gunakake file ing kene utawa klik kanggo browse
MP3, WAV, M4A, FLAC, MP4, MKV, MOV, WebM — nganti 2GB
Muat-up file karo Pro
Ningkatake kanggo Diperbaiki
Private transcript
Chat with transcript
Buka karo Pro →
Ningkatake kanggo Diperbaiki
Recording: 0:00
Wektu nyata Lilin (sekarang)
Dioptimalake Wisp (akurat)
Link umum: 24h, teks mung · Ndaftar for 7d + audio · Pro for private links

Parobihan basa kana teks. AI ngalereskeun otomatis nalika anjeun nyarios - akurasi naék ku kecap-kecap anu langkung panjang.

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Apa tegese dialek?

Diarisasi juru basa ya iku proses ngresiki aliran audio dadi segmen miturut identitas juru basa. Ing tembung sing luwih sederhana, iki mangjawab pitakon "siapa yang berbicara kapan?" 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.

Cara Nggunakake Pengamatan Penyiar

1. Voice Activity Detection

Sistem ieu mimitina ngaidentipikasi segment audio anu ngandung basa versus sunyi, musik, atanapi sora latar.

2. Speaker Embedding

Satiap segmentu basa dikonversi kana speaker embedding - vektor kompakt anu ngamangpaatkeun ciri vokal unik tina speaker.

3. Clustering & Labeling

Sacara umum, kecap-kecap anu dipaké dina basa Sunda digolongkeun kana tilu golongan, nyaéta kecap-kecap anu dipaké dina basa Sunda (1), basa Sunda (2), jeung basa Sunda (3).

Kasus kanggo deteksi pembicara

Transkrip Rapat
Ngalabelkeun sacara otomatis unggal pamilon dina rekaman rapat. Nyiptakeun menit kalayan attribusi anu jelas saha anu nyarios naon.
Podcast Transkripsi
Ngabédakeun antara host jeung tamu dina episode podcast. Nyiptakeun catatan acara kalayan attribusi panyatur anu pas.
Transkripsi
Diantara kagiatan anu dilaksanakeun nyaéta panalungtikan, pangembangan, publikasi, jeung pamasaran.
Hukum & Kepatuhan
Ngahasilkeun laporan resmi, depositions, audiences, jeung compliance telepon kalawan jelas speaker identifikasi.

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.

Coba deteksi pembicara saiki

Ngaupload rekaman multi-speaker sarta tingali speakers labeled sacara otomatis.

Mulai Transkripsi Gratis

Takon-takon sing asring diajukake

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.