We study the capabilities of speech processing systems trained simply to predict large
amounts of transcripts of audio on the internet. When scaled to 680,000 hours of multilingual …

The task of estimating the fundamental frequency of a monophonic sound recording, also
known as pitch tracking, is fundamental to audio processing with multiple applications in …

This paper presents Task 4 of the Detection and Classification of Acoustic Scenes and
Events (DCASE) 2019 challenge and provides a first analysis of the challenge results. The …

Affective Computing systems can detect the emotional state and mindset of an individual.
Speech Emotion Recognition (SER) is a unimodal affect computing system based on …

We propose the Probabilistic YIN (PYIN) algorithm, a modification of the well-known YIN
algorithm for fundamental frequency (F0) estimation. Conventional YIN is a simple yet …

Predictive models for music annotation tasks are practically limited by a paucity of well-
annotated training data. In the broader context of large-scale machine learning, the concept …

We present a comparative analysis of the performance of state-of-the-art sound event
detection systems. In particular, we study the robustness of the systems to noise and signal …

In this paper, we provide a new neural-network based perspective on multi-task learning
(MTL) and multi-domain learning (MDL). By introducing the concept of a semantic descriptor …

We propose and demonstrate a simple method to explain the figure of merit (FoM) of a music
information retrieval (MIR) system evaluated in a dataset, specifically, whether the FoM …

The paucity of physiological time-series data collected from low-resource clinical settings
limits the capabilities of modern machine learning algorithms in achieving high performance …