Conference Audio Filtering for Sensitive Speech Removal
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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 systems that filter or remove portions of speech based on predefined sensitive topics or undesirable language by using hash values and applying filters in real-time or during playback, ensuring sanitized audio output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional conferencing technologies are used, then the system is simple and easy to operate, but the system cannot automatically detect and prevent exposure of sensitive topics or undesirable language
Solution Approach 1:
The patent introduces an audio stream modification system that acts as an intermediary between the conference participant and other participants. This system includes audio processing components that analyze audio streams in real-time, detect sensitive topics using hash value comparison against a data store, and automatically modify or remove problematic audio segments. The intermediary system protects confidentiality without requiring changes to the core conferencing technology.
Solution Approach 2:
The patent replaces manual monitoring and moderation of conference audio with an automated digital system. The audio stream modification system uses digital signal processing, hash value generation, and automated detection algorithms to identify and filter sensitive content. This substitution of mechanical/manual processes with automated electronic systems enables reliable confidentiality protection while maintaining ease of operation.
2Reliability
If audio stream modification is implemented to remove undesirable speech, then confidentiality and professionalism are enhanced, but the device complexity increases
Solution Approach 1:
The audio stream modification system processes audio streams by dividing them into manageable segments or frames. The system analyzes audio data in discrete time windows, generates hash values for specific audio segments, and applies modifications to individual problematic segments rather than processing the entire audio stream at once. This segmentation approach reduces computational complexity while maintaining effective detection and removal of undesirable speech.
3Reliability
If real-time audio filtering is applied, then sensitive information is prevented from exposure, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing hash values of sensitive topics and undesirable language in a data store before conferences begin. During real-time conference audio processing, the system only needs to generate hash values from incoming audio and compare them against the pre-computed database, rather than performing complex analysis from scratch. This preliminary preparation significantly reduces real-time processing time while maintaining detection accuracy.
Data Source
AI summary
A portion of speech represented in an audio stream of a conference participant is removed based on a determination that the portion of the speech corresponds to language identified as undesirable. An audio stream representing speech of a user of a participant device connected to a conference is obtained. The audio stream is processed to detect that a portion of the speech corresponds to language identified as undesirable within an audio profile. A modified audio stream is produced by removing the portion of the speech from the audio stream. An output, within the conference, of the modified audio stream is then caused in place of the audio stream.