#automatic speech recognition

The application efficiently uses OpenAI Whisper for automatic speech recognition, offering near real-time performance with Next.js. It provides customizable settings for noise reduction and pause detection, supporting various languages and tasks. With clear setup instructions, the app is easy to deploy locally or via HTTPS, making it ideal for developers needing a scalable, customizable transcription solution.

Discover the capabilities of OpenAI's Whisper model for automatic speech recognition within Unity3D. Supporting approximately 60 languages, this package operates locally without an internet connection, offering language translation such as German to English. It provides various model sizes for a balance between speed and accuracy and is compatible with platforms like Windows, MacOS, Linux, iOS, Android, and VisionOS. Open-source under the MIT License, it can be used in commercial projects, with guidelines for optimizing CUDA and Metal for specific hardware.

Discover how Docker-whisperX facilitates efficient Docker management by integrating automatic speech recognition with detailed timestamps and speaker identification. Utilizing GitHub Free runner, it supports weekly parallel workflows to handle 175 Docker images of 10GB, leveraging caching and optimization strategies. Offers GPU support for Windows, Linux, and OSX, with pre-built images covering diverse language models. Supports customized image creation with specific languages, or choose Red Hat UBI for extra security and performance, making it suitable for scalable and efficient Docker usage in speech recognition applications.