Hsin‐Min Wang

Investigating Modulation Spectrum Factorization Techniques for Robust Speech Recognition

2015

The performance of an automatic speech recognition (ASR) system often deteriorates sharply due to the interference from varying environmental noise. As such, the development of effective and efficient robustness techniques has long been a challenging …

Automatic Detection of Speech Under Cold Using Discriminative Autoencoders and Strength Modeling with Multiple Sub-Dictionary Generation

2018

In this paper we aim to tackle the Cold sub-challenge proposed in the INTERSPEECH 2017 ComParE Challenge. The goal is to determine whether given speech is under cold condition. In this paper we present two …

Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages

2024 · arXiv (Cornell University)

This study investigates the efficacy of data augmentation techniques for low-resource automatic speech recognition (ASR), focusing on two endangered Austronesian languages, Amis and Seediq. Recognizing the potential of self-supervised learning (SSL) in low-resource settings, we …

Voice conversion from non-parallel corpora using variational auto-encoder

2016

We propose a flexible framework for spectral conversion (SC) that facilitates training with unaligned corpora. Many SC frameworks require parallel corpora, phonetic alignments, or explicit frame-wise correspondence for learning conversion functions or for synthesizing a …