Moonshine
Fast and accurate automatic speech recognition model for edge devices
Product Details
Moonshine is a family of speech-to-text models optimized for resource-constrained devices, ideal for real-time, on-device applications such as live transcription and voice command recognition. On the test dataset used in the OpenASR leaderboard maintained by HuggingFace, Moonshine outperforms the OpenAI Whisper model of the same size in word error rate (WER). Additionally, Moonshine's computational requirements scale with the length of the input audio, meaning shorter input audio is processed faster, unlike the Whisper model, which processes everything as 30-second chunks. Moonshine processes 10-second audio clips 5 times faster than Whisper while maintaining the same or better WER.
Main Features
How to Use
Target Users
Moonshine is suitable for users who need fast and accurate speech recognition on resource-constrained devices, such as developers, enterprises, and individuals who need real-time speech transcription services. It is especially suitable for scenarios that require voice interaction on mobile devices or IoT devices.
Examples
Developers can use Moonshine to add real-time speech recognition capabilities to mobile applications.
Businesses can integrate Moonshine into their customer service systems to provide speech-to-text services.
Individual users can use Moonshine to transcribe audio recordings of meetings or lectures.
Quick Access
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