Noise Filtering Module for Speech Recognition Background Compensation
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Solution Overview
Problem
Background noise, particularly music, interferes with the functionality of speech recognition devices in noisy environments, making it difficult for them to distinguish user voice commands from ambient audio sources.
Innovation Solution
A noise filtering module continuously monitors the environment to identify and filter out background audio data not generated by the user, creating an acoustic profile for known audio sources and comparing it to a central database to isolate and remove the background noise from the audio data received by the speech recognition device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the speech recognition device operates in noisy environments, then it can be used more widely, but background noise interferes with voice command recognition
Solution Approach 1:
The audio signal is segmented into multiple frequency bands using a filter bank, allowing the system to process different frequency ranges separately. This enables selective noise filtering while preserving speech components in specific frequency bands, thereby maintaining recognition accuracy in noisy environments.
Solution Approach 2:
The system extracts and removes background noise components from the audio signal by identifying and isolating noise patterns in the frequency spectrum. This extraction process separates the desired speech signal from unwanted environmental noise, improving voice command recognition reliability.
2Measurement precision
If background noise is filtered out, then voice command recognition accuracy improves, but the device complexity increases
Solution Approach 1:
The patent replaces complex hardware-based noise filtering systems with software-based signal processing algorithms. The filter bank and spectral analysis are implemented through computational methods rather than physical acoustic filters, reducing device complexity while maintaining or improving noise removal effectiveness.
Solution Approach 2:
The system dynamically adjusts filtering parameters based on the detected noise characteristics and speech content. By changing filter coefficients, frequency band selections, and processing intensity adaptively, the system achieves high recognition accuracy without requiring a permanently complex filtering infrastructure.
Data Source
AI summary
Compensating for identifiable background content in a speech recognition device, including: receiving, by a noise filtering module, an identification of environmental audio data received by the speech recognition device; and filtering, by the noise filtering module in dependence upon which portion of the identified environmental audio data was being rendered when the audio data generated from the plurality of sources was received, the audio data generated from the plurality of sources.