Download Hard real-time onset detection of percussive instruments To date, the most successful onset detectors are those based on frequency representation of the signal. However, for such methods the time between the physical onset and the reported one is unpredictable and may largely vary according to the type of sound being analyzed. Such variability and unpredictability of spectrum-based onset detectors may not be convenient in some real-time applications. This paper proposes a real-time method to improve the temporal accuracy of state-of-the-art onset detectors. The method is grounded on the theory of hard real-time operating systems where the result of a task must be reported at a certain deadline. It consists of the combination of a time-base technique (which has a high degree of accuracy in detecting the physical onset time but is more prone to false positives and false negatives) with a spectrum-based technique (which has a high detection accuracy but a low temporal accuracy). The developed hard real-time onset detector was tested on a dataset of single non-pitched percussive sounds using the high frequency content detector as spectral technique. Experimental validation showed that the proposed approach was effective in better retrieving the physical onset time of about 50% of the hits detected by the spectral technique, with an average improvement of about 3 ms and maximum one of about 12 ms. The results also revealed that the use of a longer deadline may capture better the variability of the spectral technique, but at the cost of a bigger latency.
Download High frequency magnitude spectrogram reconstruction for music mixtures using convolutional autoencoders We present a new approach for audio bandwidth extension for music signals using convolutional neural networks (CNNs). Inspired by the concept of inpainting from the field of image processing, we seek to reconstruct the high-frequency region (i.e., above a cutoff frequency) of a time-frequency representation given the observation of a band-limited version. We then invert this reconstructed time-frequency representation using the phase information from the band-limited input to provide an enhanced musical output. We contrast the performance of two musically adapted CNN architectures which are trained separately using the STFT and the invertible CQT. Through our evaluation, we demonstrate that the CQT, with its logarithmic frequency spacing, provides better reconstruction performance as measured by the signal to distortion ratio.
Download A Feedback Canceling Reverberator A real-time auralization system is described in which room sounds are reverberated and presented over loudspeakers. Room microphones are used to capture room sound sources, with their outputs processed in a canceler to remove the synthetic reverberation also present in the room. Doing so suppresses feedback and gives precise control over the auralization. It also allows freedom of movement and creates a more dynamic acoustic environment for performers or participants in music, theater, gaming, and virtual reality applications. Canceler design methods are discussed, including techniques for handling varying loudspeaker-microphone transfer functions such as would be present in the context of a performance or installation. Tests in a listening room and recital hall show in excess of 20 dB of feedback suppression.