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ການກວດພົບ​ຜູ້​ເວົ້າ ແລະ ການ​ບັນທຶກ​ລາຍ​ວັນ

ກວດພົບ ແລະ ວາງស្លាກຜູ້ເວົ້າທີ່ແຕກຕ່າງໃນ​ການ​ແປສຽງ ແລະ ວີດີໂອ​ຂອງທ່ານ​ໂດຍ​ອັດຕະໂນມັດ. ຮູ້​ຢ່າງ​ແນ່ນອນ​ວ່າ​ຜູ້​ໃດ​ເວົ້າ​ຫຍັງ.

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ປັບປຸງ​ໃຫ້​ດີ​ຂຶ້ນ
ການບັນທຶກ & # 160; ៖ 0:00
ເວລາ​ຈິງ ແກ້ວ​ຝ້າຍ (ຊົ່ວຄາວ)
ເພີ່ມ​ປະສິດທິພາບ ສຽງ​ຊົ່ວ​ຄາວ (ຖືກຕ້ອງ)
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ສຽງ​ເປັນ​ຂໍ້​ຄວາມ​ໃນ​ເວລາ​ຈິງ. AI ​ແກ້​ຂໍ້​ຜິດພາດ​ໂດຍ​ອັດຕະໂນມັດ​ເມື່ອ​ທ່ານ​ເວົ້າ - ຄວາມ​ຖືກຕ້ອງ​ຈະ​ດີ​ຂຶ້ນ​ເມື່ອ​ທ່ານ​ເວົ້າ​ດົນ​ກວ່າ.

ທົດສອບ​ໄມໂຄຣໂຟນ​ຂອງທ່ານ​ກ່ອນ
❤️ ຮັກ STT.ai? ເວົ້າກັບເພື່ອນຂອງທ່ານ!
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ຫຍັງຄືການ​ເຮັດ​ໃຫ້​ຜູ້​ເວົ້າ​ເວົ້າ​ໄດ້?

ການ​ແບ່ງ​ແຍກ​ຜູ້​ເວົ້າ​ແມ່ນ​ຂັ້ນຕອນ​ຂອງການ​ແບ່ງ​ແຍກ​ສູດ​ສຽງ​ເປັນ​ສ່ວນ​ຕ່າງໆ​ຕາມ​ຕົວ​ຕົນ​ຂອງ​ຜູ້​ເວົ້າ​. ໃນ​ຄຳ​ສັບ​ທີ່​ງ່າຍ​ຂຶ້ນ, ມັນ​ຕອບ​ຄຳ​ຖາມ "ຜູ້​ໃດ​ເວົ້າ​ເມື່ອ​ໃດ?" 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.

ການກວດພົບຜູ້ເວົ້າເຮັດວຽກແນວໃດ

1. ການກວດພົບກິດຈະກໍາສຽງ

ລະບົບ​ຈະ​ກວດ​ພົບ​ກ່ອນ​ອື່ນ​ໝົດ​ວ່າ​ພາກ​ຂອງ​ສຽງ​ໃດ​ມີ​ການ​ເວົ້າ​ທຽບ​ກັບ​ຄວາມ​ງຽບ, ດົນຕີ ຫຼື ສຽງ​ລົບ​ໃນ​ພື້ນ​ຫຼັງ.

2. ບັນຈຸບັນທຶກ

ແຕ່ລະສ່ວນຂອງສຽງຈະຖືກປ່ຽນເປັນສຽງຂອງຜູ້ເວົ້າ -- ເວັກເຕີທີ່ນ້ອຍທີ່ສຸດທີ່ບັນທຶກຄຸນລັກສະນະສຽງທີ່ເປັນເອກະລັກຂອງຜູ້ເວົ້າ.

3. ການ​ຈັດ​ກຸ່ມ ແລະ ​ການ​ວາງ​ស្លាກ

ການ​ຝັງ​ແມ່ນ​ຖືກ​ຈັດ​ເປັນ​ກຸ່ມ​ເພື່ອ​ຈັດ​ກຸ່ມ​ສ່ວນ​ຈາກ​ຜູ້​ເວົ້າ​ດຽວ​ກັນ​ພ້ອມ​ກັນ, ຫຼັງຈາກນັ້ນ​ກຸ່ມ​ແຕ່ລະ​ອັນ​ຈະ​ຖືກ​ມອບ​ໃຫ້​ມີ​ស្លាກ (ຜູ້ເວົ້າ 1, ຜູ້ເວົ້າ2ແລະ​ອື່ນໆ) & # 160; ។

ກໍລະນີ​ໃຊ້​ງານ​ສຳລັບ​ການ​ກວດ​ພົບ​ຜູ້​ເວົ້າ

ບັນທຶກ​ການ​ປະຊຸມ
ວາງ​ស្លាກ​ຜູ້ເຂົ້າຮ່ວມ​ແຕ່ລະຄົນ​ໃນ​ການບັນທຶກ​ການ​ປະຊຸມ​ໂດຍ​ອັດຕະໂນມັດ. ສ້າງ​ບົດບັນທຶກ​ດ້ວຍ​ການ​ອະທິບາຍ​ທີ່​ຈະແຈ້ງ​ວ່າ​ຜູ້ໃດ​ເວົ້າ​ຫຍັງ
ແປ​ເປັນ​ພາສາ​ໂປດ​ແກຣມ
ແບ່ງປັນ​ລະຫວ່າງ​ຜູ້​ຈັດການ ແລະ ແຂກ​ໃນ​ບົດ​ເພງ​ໂປດ​ແກຣມ. ສ້າງ​ບັນທຶກ​ການ​ສະແດງ​ດ້ວຍ​ການ​ອະທິບາຍ​ຜູ້​ເວົ້າ​ທີ່​ຖືກຕ້ອງ.
ບົດບັນທຶກການສຳພາດ
ສໍາພາດຜູ້ສໍາພາດແລະຕອບສໍາພາດສໍາລັບການຄົ້ນຄວ້າ, ສື່, ແລະເອກະສານຈ້າງງານ.
ກົດໝາຍ ແລະ ການປະຕິບັດ
ສ້າງບັນທຶກທາງການຂອງຄໍາໃຫ້ການ, ການຟັງ, ແລະ ການໂທຕາມກົດຫມາຍກັບຜູ້ເວົ້າທີ່ລະບຸຢ່າງຈະແຈ້ງ.

ການກວດພົບ​ຜູ້​ເວົ້າ​ໃນ 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.

ພະຍາຍາມ​ກວດພົບ​ຜູ້​ເວົ້າ​ດຽວ​ນີ້

ສົ່ງ​ການບັນທຶກ​ຫຼາຍ​ໄມໂຄຣໂຟນ​ຂຶ້ນ​ໄປ ແລະ ເບິ່ງ​ໄມໂຄຣໂຟນ​ທີ່​ມີ​ស្លាກ​ໂດຍ​ອັດຕະໂນມັດ.

ເລີ່ມຕົ້ນ​ການ​ແປ​ເປັນ​ພາສາ​ຟຣີ

ຄໍາຖາມທີ່ຖາມເລື້ອຍໆ

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.