Famantarana & Diarization

Mamaritra sy mamaritra hoazy ireo mpiteny isan-karazany ao anatin'ny dika mitovy amin'ny feo sy ny lahatsary. Fantaro mazava tsara hoe iza no nilaza inona.

Miasa amin'ny feo sy horonantsary azo idirana ho an'ny rehetra. Tsy raisina an-tànana ny votoaty voaaro amin'ny DRM.

Handefa ny fanatsarana
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Fandraiketana: 0:00
Fotoana tena izy Vao haingana
Nohavaozina Hihomehy (tsy diso)
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Fiteny mankany amin'ny soratra amin'ny fotoana tena izy. Mitsara ny teny rehefa miteny ianao — mitombo ny marina rehefa lava ny teny.

Manandrana ny microphone-nao aloha
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Inona no atao hoe Speaker Diarization?

Ny diarization dia ny fomba fizarazarana ny feo ho ampahany araka ny maha-izy azy ny mpiteny, amin'ny teny tsotra, mamaly ny fanontaniana hoe "iza no niteny ary oviana?" 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.

Ny fomba fiasan'ny fitadiavana ny mpiteny

1. Famantarana ny asa amin'ny feo

Ny fiteny dia fiteny izay mampiasa ny feo, ny feo na ny feo.

2. Fampidirana ny mpandahateny

Ny fiteny dia mizara ho sokajy marobe, izay samy manana ny fiteny fototra izay mahatonga azy ireo ho fiteny miavaka.

3. Fampivondronana sy famaritana

Ny fiteny dia mizara ho sokajy roa, ny voalohany dia ny fiteny fototra (izay ahitana ny fiteny rehetra), ny faharoa dia ny fiteny fototra (izay ahitana ny fiteny rehetra).

Fomba fampiasana ny fijerena ny mpiteny

Fandikana ny laha-tahirin'ny fivoriana
Mamaritra hoazy ny mpandray anjara tsirairay anatin'ny fandraiketana ny fivoriana. Mamorona tatitra misy ny anaran'ny olona nilaza ny zavatra.
Fandikana podcast
Mamaritra ny mpikarakara sy ny vahiny anatin'ny fizarana podcast. Mamorona taratasin-tadidy miaraka amin'ny famaritana ny mpiteny.
Dikanteny amin'ny tafatafa
Mizarazara ny valinteny avy amin'ny mpandray anjara sy ny mpandray anjara ho an'ny fikarohana, ny fanaovan-gazety, ary ny tahirin-kevitra momba ny fividianana.
Ara-dalàna & Fanentanana
Mamorona tahirin-kevitra ofisialy momba ny fijoroana vavolombelona, ny fitsapan-kevi-bahoaka, ary ny antso fanarahan-dalàna miaraka amin'ny famantarana mazava ny mpitondra tenin'ny olona.

Famantarana ny mpandahateny amin'ny 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.

Andramo ny famantarana ny mpandahateny izao

Akaro ny fandraketana amin'ny mpiteny maro ary jereo ireo mpiteny voasoratra anarana hoazy.

Manomboka ny fandikana maimaimpoana

Fanontaniana matetika

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.