Keystroke Noise Suppression via Frequency Domain Analysis
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Solution Overview
Problem
Existing technologies fail to effectively suppress keystroke noise in real-time communication environments due to variability across users and devices, and previous methods are computationally expensive, making them unsuitable for low-latency applications.
Innovation Solution
A keystroke noise suppression system that identifies keystroke noise by analyzing audio frames transformed into the frequency domain and utilizes keystroke information from an input device API to apply a suppression gain only when keystroke noise is detected in the absence of speech, without attempting to model the noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If keystroke noise is suppressed by explicitly modeling and removing it from the audio stream, then noise suppression effectiveness is improved, but computational complexity increases significantly
Solution Approach 1:
The patent extracts and removes the harmful keystroke noise component from the audio stream by detecting impulsive noise characteristics and applying suppression algorithms specifically targeted at keystroke noise patterns, separating the noise removal function from general audio processing
Solution Approach 2:
The patent changes key processing parameters including noise threshold levels, suppression gain values, and frame analysis parameters to optimize the balance between noise suppression effectiveness and computational load, allowing adaptive adjustment based on detected noise conditions
2Object-affected harmful factors
If keystroke noise is suppressed by explicit modeling and removal, then noise suppression effectiveness is improved, but processing time increases making it unsuitable for real-time communication
Solution Approach 1:
The patent performs preliminary actions by continuously monitoring audio frames for impulsive noise characteristics and pre-calculating suppression parameters before actual noise removal is needed, so that when keystroke noise is detected, suppression can be applied immediately with minimal additional processing delay
Solution Approach 2:
The patent implements a streamlined processing path that skips complex noise modeling steps and directly applies suppression algorithms when impulsive noise is detected, rushing through the essential suppression steps without unnecessary computational overhead to meet real-time latency requirements
3Adaptability or versatility
If a microphone is built into the computer and located close to the keyboard, then device integration is improved, but susceptibility to keystroke noise increases
Solution Approach 1:
The patent introduces an intermediary noise suppression processing stage between the built-in microphone and the audio output, which detects and removes keystroke noise components before the audio is transmitted or played back, mediating the conflict between close microphone placement and noise susceptibility
Data Source
AI summary
An audio signal is received that might include keyboard noise and speech. The audio signal is digitized and transformed from a time domain to a frequency domain. The transformed audio is analyzed to determine whether there is likelihood that keystroke noise is present. If it is determined there is high likelihood that the audio signal contains keystroke noise, a determination is made as to whether a keyboard event occurred around the time of the likely keystroke noise. If it is determined that a keyboard event occurred around the time of the likely keystroke noise, a determination is made as to whether speech is present in the audio signal around the time of the likely keystroke noise. If no speech is present, the keystroke noise is suppressed in the audio signal. If speech is detected in the audio signal or if the keystroke noise abates, the suppression gain is removed from the audio signal.