We present recent developments in the openSMILE feature extraction toolkit. Version 2.0
now unites feature extraction paradigms from speech, music, and general sound events with …

Smartphones and tablets have become ubiquitous in our daily lives. Smartphones, in
particular, have become more than personal assistants. These devices have provided new …

Decoding speech from brain activity is a long-awaited goal in both healthcare and
neuroscience. Invasive devices have recently led to major milestones in this regard: deep …

SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to facilitate the
research and development of neural speech processing technologies by being simple …

Brain–computer interfaces (BCIs) can restore communication to people who have lost the
ability to move or speak. So far, a major focus of BCI research has been on restoring gross …

Speaker modeling is essential for many related tasks, such as speaker recognition and
speaker diarization. The dominant modeling approach is fixed-dimensional vector …

Generating musical audio directly with neural networks is notoriously difficult because it
requires coherently modeling structure at many different timescales. Fortunately, most music …

A considerable challenge in applying deep learning to audio classification is the scarcity of
labeled data. An increasingly popular solution is to learn deep audio embeddings from large …

Clipper: A Low-Latency Online Prediction Serving System Page 1 This paper is included in the
Proceedings of the 14th USENIX Symposium on Networked Systems Design and Implementation …

We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016
edition with the aim of providing a common framework for evaluating and comparing …