Voice Quality Estimation Using Burst Loss Sequence Mapping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional voice quality estimation methods, such as the E-model, fail to accurately capture sudden quality degradation caused by burst-like packet losses, and do not effectively quantify the influence of packet losses that occur in a specific range, leading to inaccurate voice quality assessment.
Innovation Solution
A voice quality estimation apparatus that creates sequences reflecting characteristics of immediate quality degradation perception, degradation likelihood, and packet loss concealment, and calculates degradation amounts per unit time using a mapping function to estimate user-experienced voice quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the E-model uses average burst loss length (BurstR) for voice quality estimation, then the calculation is simplified and can be performed with basic network parameters, but it cannot accurately capture sudden quality degradation caused by different burst loss distributions
Solution Approach 1:
The patent segments the packet loss sequence into individual loss events with specific temporal positions and intervals. Instead of using a single average BurstR value, the method divides the loss pattern into discrete elements (loss positions, inter-loss intervals) that can be individually analyzed and weighted according to their impact on perceived quality, thereby capturing distribution characteristics while maintaining computational feasibility.
Solution Approach 2:
The patent transforms the traditional single-parameter BurstR approach into a multi-parameter model that includes loss position, inter-loss interval, and weighted degradation amounts. By changing from an average-based parameter to a set of distributed parameters with different weights, the system can accurately represent different burst loss distributions and their impact on voice quality perception.
2Ease of operation
If the evaluation criterion monotonically increases degradation amount with continuous packet loss period, then the calculation method is straightforward, but it cannot accurately grasp the influence of packet losses that suddenly occur all at once in a certain range
Solution Approach 1:
The patent applies local quality by assigning different weights to different positions and intervals within the packet loss sequence. Instead of uniform treatment of all losses, the method gives higher weights to losses that occur in positions perceived as more impactful by users (e.g., silent periods, transition regions) and uses different weighting for inter-loss intervals, thereby accurately capturing the localized impact of burst losses while maintaining a systematic evaluation framework.
3Device complexity
If conventional voice quality estimation methods are used, then the implementation is simple and relies on basic network indicators, but sudden quality degradation caused by burst-like packet losses cannot be accurately captured
Solution Approach 1:
The patent introduces dynamics by making the degradation amount variable based on loss position and inter-loss interval characteristics. The weighting factors are not static but adapt according to the specific pattern of packet losses, allowing the system to dynamically respond to different burst loss scenarios. This dynamic approach improves detection reliability for sudden quality degradation while keeping the underlying calculation framework relatively simple.
Data Source
AI summary
A voice quality estimation apparatus includes: a packet sequence creation unit configured to create a first sequence by applying a first characteristic indicating that quality degradation caused by packet loss is perceived by a user all at once, to a sequence consisting of elements each indicating whether or not a packet of a voice call has been lost; a smoothing unit configured to create a second sequence from the first sequence; a degradation amount emphasis unit configured to create a third sequence from the second sequence; a packet loss tolerance characteristics reflection unit configured to create a fourth sequence from the third sequence; a degradation amount calculation unit configured to calculate a degradation amount from the fourth sequence; and a listening quality estimation unit configured to estimate voice quality that is to be experienced by the user, from the degradation amount.