Checksub vs Whisper

Checksub provides AI-powered subtitles, dubbing, and voice-over for videos through web, API, and extension platforms. It can create subtitles automatically or synchronize subtitles from a script, and it offers subtitle translation in 200 languages. Its dubbing replaces the original voice while keeping the audio background; Checksub also says users can substitute a cloned voice in 30 languages. The online editor lets users revise and regenerate sentences after subtitle or dubbing generation. Subtitles can be burned into exported videos with animated styles, including karaoke animation. Translated-video publishing to YouTube is supported, and the Starter plan connects one channel. Listed integrations include YouTube, Twitch, Google Drive, Adobe Premiere Pro, DaVinci Resolve, and Final Cut Pro. Credit use varies by task: one credit minute per video minute for subtitles, three for dubbing, and five for lip-sync. The service has a free plan and free trial. Checksub was founded in 2017 and is headquartered in France.

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.