Automatic Level Control for Speech Signals Using Sub-Frame Gain
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Solution Overview
Problem
Existing speech processing technologies lack effective automatic level control (ALC) methods that can dynamically adjust amplification for speech signals without human intervention, leading to inconsistent audio quality and potential distortion.
Innovation Solution
The implementation of a digital processing block that divides audio signals into sub-frames, examines adjacent sub-frames to determine peak values, computes a gain factor based on desired maximum values, and amplifies each sample accordingly, using a combination of peak detection, proportional-integral filtering, and energy analysis to differentiate between speech and non-speech portions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automatic level control is implemented to dynamically adjust amplification of speech signals, then audio quality consistency is improved, but device complexity increases
Solution Approach 1:
The audio signal is divided into frames, with each frame containing multiple sub-frames. This segmentation allows the system to process and control different portions of the speech signal independently, improving audio quality consistency without requiring a completely complex monolithic processing system. The patent applies this by dividing the input signal into manageable units that can be processed through the ALC algorithm separately.
Solution Approach 2:
The system dynamically adjusts the gain factor for each frame based on real-time analysis of peak values and energy measurements. This dynamic adaptation allows the ALC to respond to varying speech characteristics, maintaining consistent audio quality across different input levels while avoiding the need for static, overly complex control mechanisms.
2Measurement precision
If peak detection and energy analysis are used to differentiate speech from non-speech portions, then speech signal accuracy is improved, but computational requirements increase
Solution Approach 1:
The system performs peak detection and energy analysis selectively on representative portions of the signal (sub-frames within frames) rather than processing every single sample with full computational intensity. This partial application of complex operations maintains speech detection accuracy while reducing overall computational energy consumption.
Solution Approach 2:
The system performs preliminary energy analysis and peak detection on sub-frames to identify speech portions before applying full processing. This preliminary action allows the system to prepare and classify signal portions in advance, improving measurement precision while distributing computational load efficiently.
3Manufacturing precision
If gain factor is computed based on peak values from multiple adjacent sub-frames, then distortion is reduced, but processing time increases
Solution Approach 1:
The system computes peak values and energy measurements for multiple adjacent sub-frames in advance before determining the final gain factor. This preliminary computation of intermediate values allows for more precise amplification control while organizing the processing steps to minimize overall processing time through efficient data reuse.
Solution Approach 2:
The system merges the analysis of multiple adjacent sub-frames to determine a single gain factor for a frame, combining information from several measurements to achieve better precision. This merging approach reduces the total number of separate processing operations compared to treating each sub-frame independently, thereby reducing processing delay while maintaining amplification precision.
Data Source
AI summary
Automatic level control of speech portions of an audio signal is provided. An audio signal is received in the form of a sequence of samples and may contain speech portion and non-speech portions. The sequence of samples is divided into a sequence of sub-frames. Multiple sub-frames adjacent to a present sub-frame are examined to determine a peak value of samples in the sub-frames. A gain factor is computed for the present sub-frame based on the peak value and a desired maximum value for said speech portion, and each sample in the present sub-frame is amplified by the gain factor. In an embodiment, variations in filtered energy values of multiple sub-frames enable determination of whether a sub-frame corresponds to a speech or non-speech/noise portion.