Karaoke Scoring Prediction Using Pitch Pattern Learning
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Solution Overview
Problem
Conventional karaoke prediction devices struggle to accurately predict scoring results for new musical pieces due to their inability to effectively reflect a user's singing tendency based on pitch patterns, limiting the accuracy of the prediction.
Innovation Solution
A prediction device that builds a learning model using past scoring results and pitch information for each section of musical pieces, allowing it to predict scoring outcomes for new pieces by inputting their pitch information into the model, thereby reflecting the user's scoring trend.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a result of scoring is predicted on the basis of a result of scoring of a musical piece of which a degree of difficulty is close, then the prediction can be made using simple comparison methods, but the accuracy of the prediction is limited because it cannot reflect the user's singing tendency according to pitch patterns
Solution Approach 1:
The patent transforms the prediction approach by changing the parameters used for prediction. Instead of using only degree of difficulty as a parameter, the system incorporates pitch information and pitch patterns as additional parameters. The learning model processes pitch sequences and patterns to capture the user's singing tendencies, thereby improving prediction accuracy while managing model complexity through efficient data representation and processing.
2Loss of information
If pitch information and detailed scoring data are incorporated into the prediction model, then the user's singing tendency can be reflected more accurately, but the data processing complexity and model building requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the musical piece into sections and analyzing pitch information section by section. The scoring result is also divided into section-based scores that correspond to specific pitch patterns. This segmentation allows the learning model to process large amounts of pitch data in manageable units, reducing overall data processing complexity while preserving detailed singing tendency information across different sections of the musical piece.
Data Source
AI summary
An object is to improve accuracy of prediction of a result of scoring relating to user's singing of a new musical piece. A prediction device is a device that acquires a result of scoring relating to a user's singing of a musical piece in the past for each section of the musical piece in time, acquires pitch information representing pitches of notes configuring the musical piece and aligned in a time series in the section, builds a learning model predicting a result of scoring relating to the user's singing of a musical piece from the pitch information using the result of scoring and the pitch information as training data, and acquires a result of scoring relating to the user's singing of a new musical piece on the basis of an output of the learning model by inputting the pitch information about the new musical piece to the learning model.