Deep Learning for Audio Signal Processing

Python For Audio Signal Processing

This paper discusses the use of Python for developing audio signal processing applications. Overviews of Python language, NumPy, SciPy and Matplotlib are given, which together form a powerful platform for scientific computing. We then show how SciPy was used to create two audio programming libraries, and describe ways that Python can be integrated with the SndObj library and Pure Data, two exis...

Audio Signal Processing

Perceptual audio loss function for deep learning

PESQ, Perceptual Evaluation of Speech Quality [5], and POLQA, Perceptual Objective Listening Quality Assessment [1] , are standards comprising a test methodology for automated assessment of voice quality of speech as experienced by human beings. The predictions of those objective measures should come as close as possible to subjective quality scores as obtained in subjective listening tests, us...

Machine Learning for Signal Processing

The 25th MLSP workshop in the series of workshops organized by the IEEE Signal Processing Society MLSP Technical Committee will present the most recent and exciting advances in machine learning for signal processing through keynote talks, tutorials, as well as special and regular single-track sessions. Prospective authors are invited to submit papers on relevant algorithms and applications incl...

Laboratory of Acoustics and Audio Signal Processing