265 citations · 1.9k across the 79 of their papers we have counts for
10 papers · 1 filter
On the Interplay Between Sparsity, Naturalness, Intelligibility, and Prosody in Speech Synthesis
Cheng-I Jeff Lai, Erica Cooper, Yang Zhang +8
Are end-to-end text-to-speech (TTS) models over-parametrized? To what extent can these models be pruned, and what happens to their synthesis capabilities? This work serves as a sta…
Understanding Interlocking Dynamics of Cooperative Rationalization
Mo Yu, Yang Zhang, Shiyu Chang +1
Selective rationalization explains the prediction of complex neural networks by finding a small subset of the input that is sufficient to predict the neural model output. The selec…
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding
Sijia Wang, Mo Yu, Shiyu Chang +2
Event extraction is typically modeled as a multi-class classification problem where event types and argument roles are treated as atomic symbols. These approaches are usually limit…
Global Rhythm Style Transfer Without Text Transcriptions
Kaizhi Qian, Yang Zhang, Shiyu Chang +4
Prosody plays an important role in characterizing the style of a speaker or an emotion, but most non-parallel voice or emotion style transfer algorithms do not convert any prosody…
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao, Shiyu Chang, Regina Barzilay
While unbiased machine learning models are essential for many applications, bias is a human-defined concept that can vary across tasks. Given only input-label pairs, algorithms may…
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu +7
Self-supervised speech representation learning (speech SSL) has demonstrated the benefit of scale in learning rich representations for Automatic Speech Recognition (ASR) with limit…
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
We propose Predict then Interpolate (PI), a simple algorithm for learning correlations that are stable across environments. The algorithm follows from the intuition that when using…
Complementary Evidence Identification in Open-Domain Question Answering
Xiangyang Mou, Mo Yu, Shiyu Chang +3
This paper proposes a new problem of complementary evidence identification for open-domain question answering (QA). The problem aims to efficiently find a small set of passages tha…
Generating Adversarial Computer Programs using Optimized Obfuscations
Shashank Srikant, Sijia Liu, Tamara Mitrovska +4
Machine learning (ML) models that learn and predict properties of computer programs are increasingly being adopted and deployed. These models have demonstrated success in applicati…
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up
Yifan Jiang, Shiyu Chang, Zhangyang Wang
The recent explosive interest on transformers has suggested their potential to become powerful "universal" models for computer vision tasks, such as classification, detection, and…