Speakerphone Beamforming with Nulls for Noise Exclusion
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Solution Overview
Problem
Speakerphones face challenges in acoustic echo cancellation, noise suppression, device location tracking, and proximity effect compensation, which affect the quality of voice communication and data transfer.
Innovation Solution
A method involving a virtual broadside scan to identify acoustic sources, classify them as intelligence or noise, and generate virtual beams with nulls to exclude noise sources, while tracking talkers and adjusting for proximity effects, enhancing signal quality and data transfer efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic echo cancellation is performed to improve voice intelligibility, then the received signal becomes more intelligible, but the system complexity increases
Solution Approach 1:
The patent segments the acoustic signal processing into distinct functional components: echo cancellation module, noise suppression module, and beamforming module. Each module handles specific aspects of signal processing independently, making the overall complex system more manageable and maintainable while achieving high voice intelligibility
Solution Approach 2:
The patent introduces intermediate processing stages including spectral analysis, adaptive filtering, and signal decomposition as mediators between the raw microphone input and final output. These intermediary processes break down the complex cancellation task into manageable steps, reducing overall system complexity
2Measurement precision
If noise suppression is applied to exclude noise sources, then voice quality improves, but the device complexity increases
Solution Approach 1:
The patent applies noise suppression selectively to specific frequency bands and time segments where noise is detected, rather than uniformly processing the entire signal. This localized approach improves voice quality in noisy regions while maintaining simplicity in clean regions, reducing overall computational complexity
Solution Approach 2:
The patent implements partial noise suppression by targeting only the most prominent noise sources identified through spectral analysis, rather than attempting to suppress all noise equally. This selective partial action achieves significant voice quality improvement with reduced computational burden
3Object-affected harmful factors
If beamforming with nulls is used to suppress noise sources, then noise suppression effectiveness increases, but the algorithm complexity increases
Solution Approach 1:
The patent segments the beamforming process into direction-of-arrival estimation, null placement calculation, and adaptive weight adjustment. This segmentation allows each sub-algorithm to be optimized independently, improving noise suppression effectiveness while keeping individual algorithm components relatively simple
Solution Approach 2:
The patent performs preliminary direction-of-arrival estimation and noise source localization before implementing the full beamforming with nulls. This preliminary action identifies target directions and noise sources in advance, simplifying the subsequent null placement and weight calculation algorithms
Data Source
AI summary
A communication system (e.g., a speakerphone) includes an array of microphones, a speaker, memory and a processor. The processor may perform a virtual broadside scan on the microphone array and analyze the resulting amplitude envelope to identify acoustic source angles. Each of the source angles may be further investigated with a directed beam (e.g., a hybrid superdirective/delay-and-sum beam) to obtain a corresponding beam signal. Each source may be classified as either intelligence or noise based on an analysis of the corresponding beam signal. The processor may design a virtual beam pointed at an intelligence source and having nulls directed at one or more of the noise sources. Thus, the virtual beam may be highly sensitive to the intelligence source and insensitive to the noise sources.