Learn More
A novel audio fingerprinting method that is highly robust to Time Scale Modification (TSM) and pitch shifting is proposed. Instead of simply employing spectral or tempo-related features, our system is based on computer-vision techniques. We transform each 1-D audio signal into a 2-D image and treat TSM and pitch shifting of the audio signal as stretch and(More)
As the literature on heart rate variability (HRV) continues to burgeon, so too do the challenges faced with comparing results across studies conducted under different recording conditions and analysis options. Two important methodological considerations are (1) what sampling frequency (SF) to use when digitizing the electrocardiogram (ECG), and (2) whether(More)
Singing voice separation from accompaniment in monaural music recordings is a crucial technique in music information retrieval. A majority of existing algorithms are based on singing pitch detection, and take the detected pitch as the cue to identify and separate the harmonic structure of the singing voice. However, as a key yet undependable premise, vocal(More)
Methods based on moments and moment invariants have been extensively used in image analysis tasks but rarely in audio applications. However, while images are typically two-dimensional (2D) and audio signals are one-dimensional (1D), many studies have showed that image analysis techniques can be successfully applied on audio after 1D audio signal is(More)
Time-scale modification and pitching shifting are two recognized challenging attacks to music copyright protection. To resist them simultaneously, a novel robust hashing method is proposed by combining the strength of music beat segmentation and chroma-based music feature. These two measures are aimed at solving the problem of desynchronization and(More)
  • 1