In smart grid era, demand side management (DSM) plays an indispensable role in
development of sustainable cities and societies. This paper presents practical challenges …

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 …

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 …

Despite recent progress in generative adversarial network (GAN)-based vocoders, where
the model generates raw waveform conditioned on acoustic features, it is challenging to …

This document describes version 0.10 of TorchAudio: building blocks for machine learning
applications in the audio and speech processing domain. The objective of TorchAudio is to …

Audio-visual speech recognition has received a lot of attention due to its robustness against
acoustic noise. Recently, the performance of automatic, visual, and audio-visual speech …

We propose a new end-to-end neural acoustic model for automatic speech recognition. The
model is composed of multiple blocks with residual connections between them. Each block …

We introduce dGSLM, the first “textless” model able to generate audio samples of naturalistic
spoken dialogues. It uses recent work on unsupervised spoken unit discovery coupled with …

We propose Guided-TTS, a high-quality text-to-speech (TTS) model that does not require
any transcript of target speaker using classifier guidance. Guided-TTS combines an …

We present ESPnet-ST, which is designed for the quick development of speech-to-speech
translation systems in a single framework. ESPnet-ST is a new project inside end-to-end …