Free Turkish Transcription
Transcribe Turkish audio and video to text with AI. Fast, accurate, and free.
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ផ្ទុកឯកសារអូឌីយ៉ូ ឬវីដេអូរបស់អ្នកឡើង និងទទួលបានអត្ថបទអត្ថបទក្នុងមួយវិនាទី ។
Open Transcriberរបៀបដែលវាធ្វើការ
- Go to the Free.ai Transcriber
- Upload your Turkish audio or video file
- Our AI automatically detects Turkish and transcribes it
- ទាញយកអត្ថបទបកប្រែរបស់អ្នកជាអត្ថបទ ឬចំណងជើងរង SRT
Turkish Transcription Features
- ✓ថាមពលដោយ faster- whisper (បានអនុញ្ញាតដោយ MIT)
- ✓Automatic Turkish language detection
- ✓គាំទ្រ MP3, WAV, MP4, M4A, FLAC និងច្រើនទៀត
- ✓បោះពុម្ពពេលវេលា និងនាំចេញចំណងជើងរង (SRT)
- ✓គ្មានដែនកំណត់ទំហំឯកសារលើផែនការដែលបានបង់
- ✓ឯកជន និងមានសុវត្ថិភាព -- ឯកសារត្រូវបានលុបបន្ទាប់ពីដំណើរការ
សេចក្ដីលម្អិតភាសា
| ភាសា | Turkish |
| កូដ ISO | tr |
| ម៉ូដែល AI | សម្លេងស្រែកលឿនជាងមុន |
| តម្លៃ | ឥតគិតថ្លៃ |
ភាសាបន្ថែម
មើលភាសាទាំងអស់សំណួរដែលសួរញឹកញាប់
Whisper large-v3-turbo handles Turkish solidly — 7-15% word error rate on benchmark audio. Expect occasional substitutions on named entities, numbers, and dense technical vocabulary; the bulk of the transcript will be correct. (Tier B, 7-15% word error rate on benchmark sets — we publish honest WER tiers rather than marketing claims.)
Yes — Turkish transcription draws from your daily free token pool first. Audio costs about 50 tokens per minute, so the anonymous daily pool covers a few hours of audio per day. Signed-in accounts get a larger pool plus 10,000 signup tokens. Past that, $1 buys 750,000 tokens (~250 hours of audio).
Turkish transcripts are returned in standard UTF-8 with the language's normal orthography.
MP3, WAV, M4A, FLAC, OGG, OPUS, and WEBM are accepted directly. For video (MP4, MOV, MKV) we extract the audio track server-side before sending it to Whisper — you do not need to convert anything yourself. Same pipeline regardless of source language, including Turkish.
Anonymous uploads cap at roughly 500 MB per file. Signed-in accounts go up to 2 GB. Duration is not a hard limit — long files are chunked automatically (30-second windows with overlap) and stitched back into a single transcript with continuous timestamps. Multi-hour Turkish recordings (podcasts, full lectures, meetings) work fine.
Yes — speaker diarization is on by default for every Turkish transcript. The output is segmented as Speaker 1 / Speaker 2 / Speaker 3 with timestamps, so interviews, panel discussions, and multi-party meetings come back labeled. Diarization runs on a separate model and works the same across all languages we support.
Yes — paste the URL into /transcribe/youtube/ for YouTube or /transcribe/podcast/ for podcast feeds (Apple, Spotify, RSS). We download the audio, run it through Whisper with language=tr, and return the transcript with timestamps and speaker labels. Typical Turkish content: news clips, sermons, lectures, and political interviews in Turkish are the most common workloads; paste a YouTube URL into /transcribe/youtube/ or upload the file.
Whisper costs about 50 tokens per minute of audio, so a one-hour recording is ~3,000 tokens. $1 buys 750,000 tokens, which works out to roughly 250 hours of audio per dollar. Most users never spend anything — the free daily pool covers short clips, voice notes, and one-off podcasts.
Yes — both segment-level (every ~10-30 seconds) and word-level timestamps are available. Word-level is the default for VTT/SRT subtitle export so the captions sync line-by-line. On the API set timestamps="word" in the request body. Turkish transcripts are returned in standard UTF-8 with the language's normal orthography.
Yes. POST audio (multipart/form-data, field name "file") to /v1/transcribe/ with language=tr — or omit the language parameter to let Whisper auto-detect. Returns JSON with the transcript, segments, timestamps, and speaker labels. Full reference and SDK snippets at /api/.
Yes — once transcription finishes, click Translate or paste the text into /translate/. Turkish pairs with every other language we support (200+). For meeting minutes pipe the transcript through /summarize/; for dubbing send it to /voice/tts/ to render audio in the target language.
Whisper is trained on hundreds of thousands of hours of real-world audio, so it tolerates background noise and phone-quality recordings on Turkish. For best results, supply clean audio (headset mic, no music bed) — at this tier noise compounds the baseline error rate. If a transcript comes back unusable, email contact@free.ai with the file — we will refund the tokens and look at whether a different engine handles your audio better.