Pitch, periodiciy, and noise in the voice
Music, cognition, and computerized sound
Application-Specific Music Transcription for Tutoring
IEEE MultiMedia
On the improvement of singing voice separation for monaural recordings using the MIR-1K dataset
IEEE Transactions on Audio, Speech, and Language Processing
Multipitch Analysis of Polyphonic Music and Speech Signals Using an Auditory Model
IEEE Transactions on Audio, Speech, and Language Processing
Normalized Cuts for Predominant Melodic Source Separation
IEEE Transactions on Audio, Speech, and Language Processing
Separation of Singing Voice From Music Accompaniment for Monaural Recordings
IEEE Transactions on Audio, Speech, and Language Processing
Melody Transcription From Music Audio: Approaches and Evaluation
IEEE Transactions on Audio, Speech, and Language Processing
Enhancing the Tracking of Partials for the Sinusoidal Modeling of Polyphonic Sounds
IEEE Transactions on Audio, Speech, and Language Processing
Unsupervised Single-Channel Music Source Separation by Average Harmonic Structure Modeling
IEEE Transactions on Audio, Speech, and Language Processing
Proceedings of the 2010 ACM workshop on Social, adaptive and personalized multimedia interaction and access
Context-Aware features for singing voice detection in polyphonic music
AMR'11 Proceedings of the 9th international conference on Adaptive Multimedia Retrieval: large-scale multimedia retrieval and evaluation
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
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Melody extraction algorithms for single-channel polyphonic music typically rely on the salience of the lead melodic instrument, considered here to be the singing voice. However the simultaneous presence of one or more pitched instruments in the polyphony can cause such a predominant-F0 tracker to switch between tracking the pitch of the voice and that of an instrument of comparable strength, resulting in reduced voice-pitch detection accuracy. We propose a system that, in addition to biasing the salience measure in favor of singing voice characteristics, acknowledges that the voice may not dominate the polyphony at all instants and therefore tracks an additional pitch to better deal with the potential presence of locally dominant pitched accompaniment. A feature based on the temporal instability of voice harmonics is used to finally identify the voice pitch. The proposed system is evaluated on test data that is representative of polyphonic music with strong pitched accompaniment. Results show that the proposed system is indeed able to recover melodic information lost to its single-pitch tracking counterpart, and also outperforms another state-of-the-art melody extraction system designed for polyphonic music.