Diskussjoni ħielsa biex Test Online
Ikkonverti diskors għal test b'traskrizzjoni mħaddma minn AI.Upload fajls awdjo, irrekordja mill-mikrofonu tiegħek, jew waħħal URL.100 + lingwi, 10 + mudelli, 98% + preċiżjoni.
1. ittella reġistrazzjoni tad-diskors
Ittella' fajl awdjo jew vidjo, waħħal URL, jew irreġistra diskors mill-mikrofonu tiegħek.
2. AI jikkonverti diskors għal test
Agħżel minn 10+ mudelli AI. Speaker sejbien u lingwa awtomatiku-sejbien inklużi.
3. esportazzjoni tiegħek tranżkript
Niżżel f'6 formati. Aqsam links tat-traskrizzjoni bil-plejbek tal-awdjo.
Diskussjoni għal Test Mudelli
Agħżel il-mudell tal-AI li jaqbel mal-ħtiġijiet tiegħek — jew ħallina nagħżlu l-aħjar wieħed.
Diskors għal Test f'100 + Lingwi
Lest biex jikkonvertu diskors biex test?
Ibda b'xejn →Mistoqsijiet li jsiru ta’ spiss
Diskors għal test (imsejjaħ ukoll rikonoxximent tad-diskors jew ASR) jikkonverti awdjo mitkellem fi kliem bil-miktub awtomatikament.STT.ai tmexxi reġistrazzjoni tiegħek permezz ta'mudell AI li jisma' l-awdjo u joħroġ test editjabbli b'timestamps u tikketti kelliem - l-ebda ittajpjar meħtieġ.
Mudell akustiku jimmappa l-forma tal-mewġ tal-ħoss għal fonemi, imbagħad mudell tal-lingwa jiġbor dawk fil-kliem u l-punteġġjatura l-aktar probabbli.STT.ai jagħmel dan fuq GPU b'mudelli bħal Whisper Large V3 u NVIDIA Canary, għalhekk reġistrazzjoni ta' siegħa normalment issir fi 2-3 minuti.
Iva. Kull viżitatur gets 600 minuti b'xejn fix-xahar bl-ebda sinjali meħtieġa għall-ewwel fajl tiegħek. pjanijiet imħallsa jibdew minn $5/xahar u żid fajls itwal, traskrizzjonijiet privati, u l-ipproċessar prijorità.
On clean speech our best models reach 95-97% accuracy (a 3-5% Word Error Rate on benchmarks). Accuracy drops with background noise, heavy accents, crosstalk, or low-bitrate audio — using a decent microphone and a quiet room makes the biggest difference.
Yes. Speak into your microphone and STT.ai streams the transcript live via the live-transcription tool. You can also upload a finished recording for batch transcription if you don't need it word-by-word as you talk.
STT.ai recognizes 100+ languages and auto-detects the spoken language for most audio. You can also set the language manually for a small accuracy lift, and mixed-language recordings are handled by switching mid-clip.
Yes. Speaker diarization labels each voice (Speaker 1, Speaker 2, ...) and you can rename them in the editor. This works across every supported model and language.
STT.ai accepts 20+ formats including MP3, WAV, M4A, FLAC, OGG, MP4, MKV, MOV, WebM, and AVI. Output to TXT, SRT, VTT, DOCX, JSON, or PDF.
Speech to text transcribes WHAT was said into words; voice recognition (speaker identification) determines WHO said it. STT.ai does both — transcription plus speaker diarization — but the terms describe different tasks.
Yes. Audio is processed and deleted by default. Pro plans add client-side encryption so transcripts are unreadable without your key, even to STT.ai, and your data is never used for model training without explicit opt-in.
Yes. STT.ai has a REST API with Python and Node.js SDKs plus an MCP server for Claude and Cursor. The free API tier includes 100 minutes/month, with per-second billing beyond that.
Yes. Every transcript opens in a built-in editor where you can fix misheard words, rename speakers, adjust timestamps, and add notes. Edits persist across every export format.