Audio Feature Detection via Hidden Markov Models
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Solution Overview
Problem
Conventional systems and methods fail to effectively identify and visualize musical features in audio content, such as parts, phrases, beats, and hooks, limiting users' ability to comprehend and interact with digitized audio at a deeper level.
Innovation Solution
A system utilizing physical computer processors configured with computer-readable instructions to analyze digital audio files, identify musical features through Hidden Markov Models, and display these features visually, using object definitions that reflect the type, duration, and timing of musical elements, enabling users to pinpoint and understand their occurrence within the audio content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems and methods are used for audio playback, then the system is simple and easy to operate, but the system cannot effectively identify and visualize musical features in audio content
Solution Approach 1:
The patent introduces an intermediary system comprising processors and analysis software that acts as a mediator between the audio content and the user. This intermediary performs spectral analysis, beat detection, and musical feature identification, converting raw audio data into visual representations without requiring complexity in the basic playback system.
Solution Approach 2:
The patent replaces manual mechanical analysis of audio content with automated computational methods. Digital signal processing algorithms substitute for human auditory analysis, enabling automatic identification of beats, tempo, key, and other musical features through mathematical transformation of audio data.
2Loss of information
If no musical feature identification is implemented, then the system operates quickly with minimal processing, but users cannot comprehend or interact with audio content at a deeper level
Solution Approach 1:
The patent performs preliminary analysis of audio content by pre-processing the signal to extract spectral characteristics, detect beats, and identify musical features before full playback or detailed analysis. This preliminary action prepares the data structure for faster subsequent queries and visualizations during user interaction.
Solution Approach 2:
The patent segments the audio analysis into distinct processing stages: spectral analysis, beat detection, tempo identification, key detection, and feature visualization. Each segment processes specific aspects of the audio content independently, allowing parallel processing and reducing overall computation time while preserving complete musical structure information.
Data Source
AI summary
Systems and methods for identifying musical features in audio content are presented. Audio content information may be obtained from a digital audio file, the information providing a duration for playback of the audio content and a representation of sound frequencies associated with various moments throughout the duration of the audio content. Sound frequencies associated with one or more of the moments throughout the duration of the audio content may be identified, and characteristics or patterns of the identified sound frequencies may be recognized as being indicative of one or more musical features (e.g., parts, phrases, hits, bars, onbeats, beats, quavers, semiquavers, etc.). Some implementations of the present technology define display objects for display on a digital display, the display objects provided with visual features in an arrangement that distinguishes one musical feature from another across the duration of the audio content.