Chord Identification Using Attribute-Specific Trained Models

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Solution Overview

Problem

Conventional techniques for identifying musical chords from audio signals fail to account for the attribute of the music, leading to inaccurate chord identification.

Innovation Solution

A chord identification method and apparatus that select a chord identifier corresponding to the attribute of the music, using a trained model to apply feature amounts from the audio signal, enabling precise chord identification suited to the music's genre or other attributes.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a pattern matching method is used to identify chords from audio signals, then the identification process can be performed, but the accuracy of chord identification deteriorates because music attributes are not taken into account

Engineering Contradiction:

Improvechord identification accuracyVSAvoidadaptability to different music attributes

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent segments the chord identification process by creating separate chord identifier models for different music attributes (e.g., rock, pop, jazz). Each model is specialized for a specific attribute, allowing accurate identification within that genre while maintaining overall system versatility through model selection based on detected music attributes.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the parameter of music attribute (genre type) to select appropriate chord identifier models. By detecting music attributes and switching between different identifier models corresponding to different attributes, the system achieves both high accuracy for each genre and broad adaptability across multiple genres.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If multiple chord identifier models are created for different music attributes, then chord identification accuracy for each attribute improves, but device complexity increases

Engineering Contradiction:

Improvechord identification accuracyVSAvoidnumber of chord identifier models

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent performs preliminary detection of music attributes before chord identification. By first analyzing the audio signal to determine the music attribute (genre), the system can then select the appropriate pre-prepared chord identifier model, avoiding the need to maintain and process all models simultaneously for every input.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces music attribute detection as an intermediary step between audio input and chord identification. This mediator analyzes the input signal to determine the music attribute, then uses this information to select the appropriate chord identifier model, managing complexity through intelligent routing rather than direct multi-model processing.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11322124B2Chord identification method and chord identification apparatus

Publication Date: 2022.05.03 YAMAHA CORP

AI summary

A chord identification method selects from among a plurality of chord identifiers a chord identifier that corresponds to an attribute of a piece of music represented by an audio signal, where the plurality of chord identifiers corresponds to respective ones of a plurality of attributes relating to pieces of music; and identifies a chord for the audio signal by applying a feature amount of the audio signal to the selected chord identifier.