Transkriptor vs Whisper

Transkriptor transcribes and translates audio, with support for more than 100 languages. It identifies speakers and adds timestamps, and its browser tool works with Chrome, Firefox, Microsoft Edge, and Safari. Listed inputs include MP3, MP4, and WAV; export options include TXT, SRT, PDF, DOCX, and JSON. The service claims 99% transcription accuracy. Its Lite plan costs $9.99 a month and includes 300 minutes monthly. Pro costs $19.99 a month for 2,400 minutes; Team costs $30 a month for 3,000 minutes per seat. Unused monthly minutes expire after one month, and subscriptions renew automatically unless cancelled. Meeting bots support Zoom, Google Meet, and Microsoft Teams. Storage connections include Google Drive, OneDrive, Dropbox, and Amazon S3, alongside listed integrations for CRM, project, calendar, documentation, VoIP, and collaboration apps. API access is available. Transkriptor is listed for web, iOS, Android, desktop, and browser extensions. Payments can be made by website credit card or through the App Store or Play Store.

Whisper is an open-source speech recognition model for transcription, speech translation, language identification, and voice activity detection. Its documented command-line and Python interfaces process audio files, and it can translate speech from multiple languages into English. The repository lists six model sizes—tiny, base, small, medium, large, and turbo—with different speed and memory tradeoffs; stated VRAM needs range from about 1 GB to 10 GB, depending on size. Installation is documented through pip and requires the ffmpeg command-line tool. Rust may be needed if a prebuilt tiktoken wheel is unavailable. The code and model weights are released under the MIT License, with local installation using Python and ffmpeg. Whisper is listed for Linux, macOS, Windows, and self-hosted deployment. OpenAI says it was trained on 680,000 hours of multilingual and multitask supervised data collected from the web. Performance varies widely by language, and it does not outperform models specialized for LibriSpeech. Turbo is not trained for translation; multilingual models are recommended for translating non-English speech into English.