Free-Play Song Identification Using Instrument Audio and Play History
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Solution Overview
Problem
Existing systems require users to manually select songs through interfaces, which can be distracting and disrupt the personal, emotional experience of playing music, especially when playing freely without adhering to predefined notations.
Innovation Solution
A computer-implemented method and system that allows users to start playing a song freely, and the system recognizes the song from the user's play history and real-time performance, providing musical notation, lyrics, and a backing track adjusted to the user's tempo and position in the song.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the user manually selects songs through interface menus, then the system can provide accurate song information and notation, but the user experience is disrupted and the personal emotional playing experience is compromised
Solution Approach 1:
The system automatically detects the user's playing and identifies the song without requiring manual selection through interfaces. The user simply plays their instrument and the system self-identifies the song by analyzing the audio signal and comparing it against stored musical data, eliminating the need for interface interaction during the playing experience.
Solution Approach 2:
The manual mechanical interaction of selecting songs through buttons and menus is replaced by an automated audio-based detection system. The system uses audio signal processing and pattern recognition to automatically identify songs, substituting the mechanical interface interaction with an acoustic field-based automatic identification mechanism.
2Adaptability or versatility
If the user plays freely without adhering to predefined notations, then the personal expressive experience is enhanced, but the system cannot accurately detect and identify the song
Solution Approach 1:
The system changes the parameters for song detection from requiring precise note-by-note adherence to detecting broader harmonic and rhythmic patterns. By analyzing chord progressions, tempo variations, and overall musical structure rather than exact note execution, the system can accurately identify songs even when players deviate from predefined notations.
Solution Approach 2:
Instead of requiring complete and precise note-by-note performance matching, the system uses partial pattern recognition to identify songs. By detecting characteristic musical motifs, chord sequences, and rhythmic patterns that are sufficient for identification, the system tolerates variations in individual notes and expressions while maintaining accurate song detection.
3Loss of information
If the system provides detailed note-by-note notation and lyrics during playing, then the user can reference the performance, but the user must remove their hand from the instrument to scroll through information
Solution Approach 1:
The system transitions from providing information in a linear scrolling manner requiring hand movement to displaying information in a spatial arrangement that can be perceived visually without hand interaction. Musical notation and lyrics are presented in a way that allows the user to reference information while maintaining hand position on the instrument, using visual spatial distribution rather than sequential scrolling.
4Adaptability or versatility
If the system uses chord-based music notation for free playing, then the player can play accompanying instruments at their own tempo, but the amount of information in chords is not sufficient to disambiguate the song
Solution Approach 1:
The system segments the musical information into multiple analytical dimensions: chord progression patterns, rhythmic characteristics, tempo variations, and distinctive musical motifs. By analyzing these separate segments of musical information independently and combining them for song identification, the system extracts sufficient distinguishing features even from simplified chord-based performances.
Solution Approach 2:
The system uses a universal detection approach that works across different playing styles and instrument types. The same audio analysis and pattern recognition mechanisms that work for detailed instrumental performances also function for accompanying instrument play, making the system adaptable to various performance contexts while maintaining identification accuracy.
Data Source
AI summary
A computer-implemented method for identifying a song includes: providing audio data including musical notation information for songs, receiving a real-time audio signal of a user performing on an instrument, detecting playing activity in successive segments, detecting notes and/or chords from the audio signal, storing user play history information including of information of songs a user has played before and number of plays, based on the play history information calculating a first probability for a song, based on first probabilities for a number of songs and based on the detected playing activity and the detected notes and/or chords, estimating the song being performed. The estimation includes calculating a second probability for different songs. The second probabilities are defined by the audio signal corresponding with a particular song of the play history combined with first probability associated with the song, and providing the song the user is performing or related information.