Publications (5)
Less Peaky and More Accurate CTC Forced Alignment by Label Priors
Ruizhe Huang, Xiaohui Zhang, Zhaoheng Ni +9
Connectionist temporal classification (CTC) models are known to have peaky output distributions. Such behavior is not a problem for automatic speech recognition (ASR), but it can c…
TorchAudio: Building Blocks for Audio and Speech Processing
Yao-Yuan Yang, Moto Hira, Zhaoheng Ni +20
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 a…
Performance of Multiantenna Linear MMSE Receivers in Doubly Stochastic Networks
Junjie Zhu, Siddhartan Govindasamy, Jeff Hwang
A technique is presented to characterize the Signal-to-Interference-plus-Noise Ratio (SINR) of a representative link with a multiantenna linear Minimum-Mean-Square-Error receiver i…
TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch
Jeff Hwang, Moto Hira, Caroline Chen +21
TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research and development of audio and speech technologies by providing…
Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement
Xueyao Zhang, Xiaohui Zhang, Kainan Peng +10
The imitation of voice, targeted on specific speech attributes such as timbre and speaking style, is crucial in speech generation. However, existing methods rely heavily on annotat…