Audio Discriminator for Automatic Sound Classification
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Solution Overview
Problem
Current sound recognition technologies are inefficient in distinguishing and classifying various types of sounds, such as singing, humming, recorded music, and speech, often requiring users to manually select the type of sound input, which hampers user experience and accuracy.
Innovation Solution
The implementation of an audio discriminator that classifies sound inputs into three categories (singing/humming, recorded music, and speech) and routes them to respective databases for processing, allowing users to provide any type of sound input through a unified search interface without manual selection, enabling quick recognition and identification of sound features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually select the type of sound input, then the system can process sounds more accurately, but the operation becomes more complex and time-consuming
Solution Approach 1:
The system automatically detects and classifies the type of sound input (singing, humming, recorded music, or speech) without requiring user intervention. The audio discriminator autonomously analyzes the input sound and routes it to the appropriate processing pathway, making the system self-servicing in terms of input classification.
Solution Approach 2:
The system performs preliminary classification of the sound type before the main recognition process. By detecting whether the input is singing, humming, recorded music, or speech in advance, the system prepares the appropriate processing pathway beforehand, improving both accuracy and efficiency.
2Device complexity
If the system processes all sound types through a single pathway, then the device complexity is reduced, but the sound recognition accuracy deteriorates
Solution Approach 1:
The system divides the sound processing into distinct segments or pathways based on sound type. There are separate processing pathways for singing/humming sounds, recorded music, and speech, each optimized for its specific sound type. The audio discriminator determines which pathway to use based on the input sound characteristics.
Solution Approach 2:
Different processing pathways are applied to different types of sounds based on their specific characteristics. Each pathway is locally optimized for its intended sound type, with specific algorithms and databases tailored to the particular features of singing, recorded music, or speech.
3Loss of time
If the system requires manual sound type selection, then the processing time is reduced, but the ease of operation worsens
Solution Approach 1:
The system automatically performs sound type classification without requiring user time for manual selection. The audio discriminator instantly analyzes the input and routes it to the appropriate processing pathway, eliminating the time users would otherwise spend selecting sound types while maintaining ease of operation.
Solution Approach 2:
The system performs the classification action preliminarily and automatically, so that by the time the main recognition process begins, the appropriate pathway is already selected. This preliminary automatic classification eliminates delays while keeping the user experience simple.
Data Source
AI summary
Systems and methods for recognizing sounds are provided herein. User input relating to one or more sounds is received from a computing device. Instructions, which are stored in memory, are executed by a processor to discriminate the one or more sounds, extract music features from the one or more sounds, analyze the music features using one or more databases, and obtain information regarding the music features based on the analysis. Further, information regarding the music features of the one or more sounds may be transmitted to display on the computing device.