Singing Quality Assessment via Relative Pitch Rhythm Timbre Comparison
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Solution Overview
Problem
Current singing quality evaluation methods rely on standard references, such as professional vocals or digital sheet music, which are not always available, and are subjective, leading to biased and incomplete assessments that fail to capture the creativity and inherent qualities of singing.
Innovation Solution
A system and method that rank singing quality without a standard reference by combining absolute measures like pitch histograms with relative measures based on inter-singer statistics, using similarity in pitch, rhythm, and timbre to evaluate and rank singers relative to each other, enabling unbiased and comprehensive assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reference-based evaluation methods (PESnQ) are used to assess singing quality, then measurement precision is improved, but adaptability deteriorates because they require professional reference vocals or digital sheet music that are not always available
Solution Approach 1:
The system enables singers to evaluate each other's performances without requiring external reference materials. By computing relative measures that compare pitch, rhythm, and timbre across multiple recordings of the same song, the system makes the evaluation process self-sufficient and adaptable to any song regardless of reference availability
Solution Approach 2:
The patent introduces statistical models and algorithms as intermediaries that process multiple singing recordings and extract objective quality metrics. These computational intermediaries replace the need for human experts or reference vocals, enabling automated, reference-free evaluation that maintains precision while improving adaptability
2Adaptability or versatility
If expert evaluators are used to assess singing quality subjectively, then adaptability is improved as they can handle various singing styles, but measurement precision deteriorates due to subjective bias and disagreement among experts
Solution Approach 1:
The system replaces the mechanical process of human expert evaluation with an automated computational system. By substituting human subjective judgment with objective algorithms that analyze pitch histograms, rhythm patterns, and timbre characteristics, the system eliminates inter-evaluator variability while maintaining adaptability to different singing styles through feature-based analysis
Solution Approach 2:
The patent transforms the evaluation process from subjective qualitative assessment to objective quantitative measurement by changing the parameters from expert opinions to measurable acoustic features. This parameter transformation enables consistent, reproducible evaluations across different singers and songs while preserving adaptability through comprehensive feature extraction
3Device complexity
If single-measure evaluation methods are used to simplify the assessment process, then device complexity is reduced, but measurement precision deteriorates because they overlook important singing characteristics like pitch intervals and note durations
Solution Approach 1:
The evaluation system is segmented into multiple independent modules that compute different quality measures (pitch-based, rhythm-based, timbre-based). Each module focuses on specific singing characteristics, and their results are integrated to provide comprehensive evaluation. This segmentation maintains manageable complexity while achieving precise, multi-dimensional assessment
Solution Approach 2:
The patent combines multiple evaluation measures into a composite assessment framework. By integrating pitch histograms, rhythm analysis, and timbre evaluation into a unified system, the patent creates a composite measurement approach that captures the full complexity of singing quality without overwhelming system complexity through modular architecture
Data Source
AI summary
Disclosed is a system for assessing quality of a singing voice singing a song. The system comprises memory and at least one processor. The memory stores instructions that, when executed by the at least one processor, cause the at least one processor to receive a plurality of inputs comprising a first input and one or more further inputs, each input comprising a recording of a singing voice singing the song, to determine, for the first input, one or more relative measures of quality of the singing voice by comparing the first input to each further input; and to assess quality of the singing voice of the first input based on the one or more relative measures. Also disclosed is a method implemented on such a system.