Whisper by OpenAI
A neural net for speech recognition
Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web.
Reviews for Whisper by OpenAI
Hear what real users highlight about this tool.
Reviewers praise Whisper for accurate, multilingual transcription and reliability, with many noting a clear leap over older speech-to-text tools. Maker feedback highlights real-world use: makers of Voicenotes rely on it for everyday transcription; makers of Pitch Avatar say it enables smooth spoken input for avatars; makers of TalkTastic run an open-source mod both on-device and in the cloud. Users value its speed, offline options, and robustness with accents and noise, while wishing for broader client support, especially on Android.
This AI-generated snapshot distills top reviewer sentiments.
Near perfect voice note transcription
Transcription would've been impossible without Whisper!
Provides accurate, multilingual speech-to-text so users can browse hands-free—dictate, search, and control instantly. Robust even in noisy environments and with diverse accents, easy to deploy without building custom acoustic models.
Fast Best Transcription Models
Whisper provides highly accurate and multilingual speech-to-text conversion, making it perfect for turning voice commands into structured invoice data. Its reliability and ability to handle diverse accents enhance user experience across languages.
Tips: I considered Google Speech-to-Text and AssemblyAI, but Whisper stood out for its open-source flexibility, superior accuracy, and smooth integration within AI-powered apps.
This is an amazing free speech recognition engine that people can run locally and offline. We were considering alternatives like Google Speech-to-Text and AssemblyAI, but they don't offer offline capabilities, and with our vision, we wanted to create something that offers total privacy.
I used Whisper for the offline voice to text transcription. Really amazed by the quality of the output of these models.
Whisper’s speech recognition accuracy is on another level. Our audio-to-text tool wouldn’t be this good without it. Alternatives we considered: Vosk, Mozilla DeepSpeech Final thoughts: Easy to integrate, high performance even on low-resource systems. OpenAI nailed it.
We use whisper to the speech recognition and it's fantastic. It does transcribe very well in almost any language and in noisy environments like restaurants. Also it's not so expensive.
Whisper is hands-down the best voice-to-text engine I've tested. It’s accurate, supports multiple languages, and just works. It made AldeaVoice truly intelligent and reliable.
Whisper by @OpenAI has been rock solid for voicely. Clean output, great multilingual support!
Super fast and accurate for local voice transcriptions. Also, accessible through various tools. Well adopted and recognizable, making it predictable for end users.
We use Whisper under the hood for Memolith’s transcription engine. Its accuracy, especially with overlapping speech and mixed accents, was noticeably better than most other APIs we tested. It just worked—even in real-world, noisy meeting conditions. Tip: If you're building anything voice-related, Whisper is a reliable plug-and-play foundation that saves you from reinventing the wheel.