Recently, aiOla announced the launch of an open-source AI audio transcription model called Whisper-NER, which can mask sensitive information in real-time during the transcription process.
The new Whisper-NER from aiOla is built on OpenAI's industry-standard open-source model Whisper and is fully open-source. It is now available on Hugging Face and GitHub for use, adaptation, modification, and deployment by businesses, organizations, and individuals.
This audio transcription model offers flexible configuration options, allowing users to choose whether to mask sensitive information based on their needs. When users select the masking feature, the model automatically identifies and hides sensitive information such as personal names, addresses, and phone numbers, effectively preventing privacy leaks in the transcribed text. This capability makes the model particularly important for applications in fields like law, healthcare, and education.
In addition to protecting sensitive information, the model also boasts efficient and accurate transcription capabilities, functioning well across multiple languages and accents. This enhances its applicability in multilingual environments. For example, businesses can accurately record and analyze audio feedback from different regions, thereby improving service quality.
Furthermore, aiOla encourages developers and researchers to utilize this open-source model to enhance its functionality. Users can access the source code on open-source platforms and modify and optimize it according to their specific needs. This approach not only enhances the model's usability but also fosters innovation and development in AI technology.
aiOla's new product demonstrates a commitment to privacy protection in the audio transcription field and opens up more possibilities for future AI applications. With more users and developers joining in, we anticipate that this open-source model will lead to broader applications and greater impact.
Whisper-NER is fully open-source and can be used under the MIT license, allowing users to freely adopt, modify, and deploy it, including for commercial applications. Users can now also try a demo model on Hugging Face, enabling them to record voice snippets and have the model mask specific words in the generated typed script.
huggingface: https://huggingface.co/aiola/whisper-ner-v1
github: https://github.com/aiola-lab/whisper-ner
Key Points:
📌 The audio transcription model launched by aiOla can mask sensitive information in real-time, protecting user privacy.
🔍 The model supports multiple languages and accents, making it suitable for various fields such as law, healthcare, and education.
💻 The open-source nature allows users to customize and optimize the model, promoting innovation in AI technology.