Ka kitea te kaikōrero me te whakarārangitanga

Mā te whakawātea i ngā kaikōrero rerekē i roto i ōna whakamāoritanga oro me te whakaahuatanga ataata. E mōhio ana ki te mea i kī ai.

Ka mahi ki ngā oronga me ngā ataata e wātea ana ki te iwi whānui. Kāore e tautokona ngā ihirangi DRM-protected.

Whakahauhau mo te Whakarei ake
Private transcript
Kāhea me te whakahua
Whakapūkete me te Pro →
Ka tangohia te faila ki konei, ka tirohia rānei
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Whakahauhau mo te Whakarei ake
Private transcript
Kāhea me te whakahua
Whakapūkete me te Pro →
Whakahauhau mo te Whakarei ake
Te whakataki: 0:00
Wā-tūturu Wai (kore)
Whakarei ake Whisper (taurite)
Pānga tūmatanui: 24h, kupu anake · Ka whakaingoatia mō te 7d + oroiti · Ka taea mō ngā pātahitanga tūmataiti

Whakawhitiwhiti wā-tūturu ki te kupu. Ka tika te AI i te wā e kōrero ana - ka pai ake te tika me te kōrero roa.

Whakamātautau i tō tou kaihautū tuatahi
❤️ E hiahia ana ki te STT.ai? Whakapāpāho ki ōna hoa!
Kua whakamahia e koe ōna whakamāoritanga wātea

Ka whakaingoatia hei wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea mo te wātea

10 wātea min/roa 600 min wātea me te whakaingoatanga Kāore he kāri ā-pūtea Kua whakawaeheretia
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He aha te Whakahauhautanga Kaikōrero?

Ko te whakawāteatanga kaikōrero te tukanga o te whakawāteatanga o tētahi rerenga oro ki ngā wāhanga e ai ki te tuakiri o te kaikōrero. I roto i ngā kupu ngāwari ake, ka whakautua te pātai "Wā i kōrero ai?" 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.

He pēhea te mahi o te kite kaikōrero

1. Whakamāramatanga o te mahi reo

Ko te pūnaha tuatahi e mōhiotia ana he wāhanga oro he kōrero, he whakamātautau, he pūoro, he pōhēhētanga papamuri rānei.

2. Te whakatūnga kaikōrero

Ka tahuri ia wāhanga kōrero ki roto i te whakatūnga kaikōrero - he rarangi whāiti e mau ana i ngā āhuatanga oro ahurei o te kaikōrero.

3. Te whakarōpū me te tohu

Ka whakarōpūtia ngā whakatūnga kia whakarōpūtia ngā wāhanga mai i te kaikōrero ōrite, kātahi ka whakawhiwhia tētahi tohu ki ia rōpū (Kaikōrero 1, Kaikōrero 2, ērā atu mea).

Ka whakamahia ngā take mō te kite kaikōrero

Whakapānga hui
Ka whakatū i ngā tohu ā-pūtāhua mō ia kaiuru i roto i ngā pūkete hui. Ka whakaputaina ngā pūkete me te whakawhiwhinga mārama ki wai i kōrero ana.
Podcast Transcrition
He rerekē i waenganui i te kaihautū me ngā manuhiri i roto i ngā wāhanga podcast. Ka waihanga i ngā tuhipoka whakaaturanga me te whakawhiwhinga kaikōrero tika.
Whakapāpāhotanga uiui
He whakawātea te kaiuru me ngā whakautu ki te rangahau, ki te pukapuka kōrero, me te tuhinga whakawhiwhinga.
Ka whakaritea te ture me te whakaritenga
Ka waihanga i ngā pūkete ā-kāwanatanga o ngā whakapuaki, ngā whakamātautau, me ngā whakahua whakarongo me te tuakiri kōrero mārama.

Whakamāramatanga Kaikōrero i runga i te 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 whakamātau te kite kaikōrero ināianei

Whakataki i tētahi pūkete kaikōrero maha, ā, tirohia ngā kaikōrero kua whakawaengatia.

Ka tīmata te whakamāoritanga

E pā ana ngā pātai

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.