Multi-Microphone Pitch Detector Using Level Difference Clipping
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Solution Overview
Problem
Existing pitch detection technologies in communication devices are complex and resource-intensive, limiting their use in mobile applications, and traditional methods struggle with non-stationary noise environments, especially in dual-microphone platforms where complexity and processing requirements double.
Innovation Solution
A low complexity multiple microphone based pitch detector is introduced, utilizing signals from primary and secondary microphones, which includes a low pass filter, level difference detector, and adaptive clipping level determination to reduce noise and improve pitch estimation, allowing for implementation in various audio systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pitch detection methods are used in dual-microphone platforms, then pitch detection accuracy can be maintained, but computational complexity and processing requirements double
Solution Approach 1:
The pitch detection process is segmented into distinct stages: signal acquisition from primary and reference microphones, noise reference signal generation through subtraction, and pitch detection on the enhanced speech signal. This segmentation allows the system to process signals in a structured manner that reduces overall computational complexity while maintaining accuracy
Solution Approach 2:
The system performs preliminary noise reduction by combining the primary signal with the inverted reference noise signal before pitch detection. This preliminary action enhances the speech signal quality in advance, making the subsequent pitch detection more accurate and potentially simpler
2Measurement precision
If traditional pitch detection methods are used, then pitch estimation can be obtained, but processing requirements become excessive for mobile applications
Solution Approach 1:
The invention extracts and removes the reference noise component from the primary signal using the reference microphone. By taking out the noise portion through signal subtraction, the system reduces the processing burden on mobile devices while preserving the essential speech information needed for accurate pitch estimation
Solution Approach 2:
Noise reduction is performed as a preliminary action before pitch detection. The system pre-processes the signals by combining primary and reference microphone inputs to reduce noise content, which simplifies the subsequent pitch detection process and reduces overall processing requirements
3Reliability
If conventional pitch detectors are applied to dual-microphone systems, then comprehensive pitch detection can be achieved, but device complexity increases
Solution Approach 1:
The system merges the primary microphone signal with the inverted reference microphone signal to create an enhanced speech signal. This combining operation integrates noise reduction and pitch detection into a unified processing pipeline, improving reliability while avoiding the need for separate complex systems
Solution Approach 2:
The pitch detection system is designed to serve multiple functions: it detects pitch for noise reduction purposes, enables voice activity detection, and provides speech coding information. This multi-functionality approach increases reliability across different audio processing tasks while sharing common processing resources to manage complexity
Data Source
AI summary
Various embodiments of multiple microphone based pitch detection are provided. In one embodiment, a method includes obtaining a primary signal and a secondary signal associated with multiple microphones. A pitch value is determined based at least in part upon a level difference between the primary and secondary signals. In another embodiment, a system includes a plurality of microphones configured to provide a primary signal and a secondary signal. A level difference detector is configured to determine a level difference between the primary and secondary signals and a pitch identifier is configured to clip the primary and secondary signals based at least in part upon the level difference. In another embodiment, a method determines the presence of voice activity based upon a pitch prediction gain variation that is determined based at least in part upon a pitch lag.