17919941. MICROSEGMENT SECURE SPEECH TRANSCRIPTION simplified abstract (MICROSOFT TECHNOLOGY LICENSING, LLC)
Contents
MICROSEGMENT SECURE SPEECH TRANSCRIPTION
Organization Name
MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor(s)
Hemant Malhotra of Newark CA (US)
Xuedong Huang of Bellevue WA (US)
Ivo Jose Garcia Dos Santos of Kirkland WA (US)
Shuangyu Chang of Davis CA (US)
MICROSEGMENT SECURE SPEECH TRANSCRIPTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17919941 titled 'MICROSEGMENT SECURE SPEECH TRANSCRIPTION
Simplified Explanation
The patent application describes a method for securing data access to machine learning training data across multiple distributed computing devices. Here is a simplified explanation of the abstract:
- The electronic content, which includes original data, is divided into smaller segments called microsegments.
- These microsegments are selectively distributed to different computing devices.
- The computing devices apply transcription labels to the microsegments.
- The labeled microsegments are then reconstructed to form the training data for a machine learning model.
- This process improves the data security of the original data included in the training data.
Potential applications of this technology:
- Enhancing data security in machine learning training processes.
- Protecting sensitive or confidential data used in machine learning models.
- Enabling secure collaboration and sharing of training data across distributed computing devices.
Problems solved by this technology:
- Ensuring the security and privacy of sensitive data during machine learning training.
- Preventing unauthorized access or leakage of confidential information.
- Facilitating secure data sharing and collaboration in distributed computing environments.
Benefits of this technology:
- Improved data security by distributing and labeling microsegments of the original data.
- Enhanced privacy protection for sensitive information used in machine learning.
- Enables secure and efficient collaboration on machine learning projects across multiple devices.
Original Abstract Submitted
Embodiments are provided for securing data access to machine learning training data at a plurality of distributed computing devices. Electronic content including original data that corresponds to a preferred data security level is divided into a plurality of microsegments. The plurality of microsegments is restrictively distributed to a plurality of computing devices which apply transcription labels to the plurality of microsegments. The labeled microsegments are reconstructed into training data which is then used to train a machine learning model while facilitating an improvement in data security of the original data included with the training data from the reconstructed microsegments.
