Conference Audio Filtering for Sensitive Topic Sanitization
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Solution Overview
Problem
Conventional conferencing technologies lack the capability to automatically detect and modify audio streams to prevent exposure of sensitive topics or undesirable language during conferences, leading to potential breaches of confidentiality and disruption.
Innovation Solution
Implementing audio stream modification software that detects predefined sensitive topics or undesirable language in real-time, applying filters to sanitize or remove such content from the audio stream, and outputting the modified stream within the conference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If audio stream modification software is implemented to detect and filter sensitive topics, then conference privacy and professionalism are improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent introduces an intermediary audio stream modification software layer between the original audio stream and the conference participants. This intermediary component detects sensitive topics using predefined keywords or machine learning models, filters them out, and replaces them with sanitized audio, thereby protecting conference privacy without requiring changes to the original audio sources or participant devices
Solution Approach 2:
The audio stream is segmented into individual audio frames or samples, which are processed independently through the sensitivity detection and filtering mechanism. This segmentation allows the system to identify and remove sensitive portions without affecting the entire audio stream, reducing the computational burden and complexity
2Reliability
If real-time audio filtering is applied to remove sensitive content, then sensitive information exposure is prevented, but processing time and latency increase
Solution Approach 1:
The system performs preliminary actions by pre-loading a database of sensitive keywords, phrases, and audio fingerprints before the conference begins. During the conference, the system only needs to compare incoming audio against this pre-prepared database, significantly reducing real-time processing time and latency while maintaining effective sensitive content detection
Solution Approach 2:
Instead of processing the entire audio stream with high computational intensity, the system applies partial action by focusing filtering only on specific audio segments that match predefined sensitive patterns or keywords. This selective filtering approach maintains information security while minimizing processing time and latency for the majority of the audio stream
Data Source
AI summary
A portion of an audio stream representing speech of a conference participant is filtered based on a determination that the portion of the audio stream corresponds to a predefined sensitive topic. An audio stream representing speech of a user of a participant device connected to a conference is obtained. First hash values are determined for portions of the speech. A determination is made, by comparing the first hash values against second hash values for records of a data store, that a portion of the speech corresponds to a predefined sensitive topic indicated within the records. A filter is applied against the portion of the speech to produce a modified audio stream within which the predefined sensitive topic is sanitized. An output, within the conference, of the modified audio stream is then caused in place of the audio stream.