Chin‐Hui Lee

Joint training of front-end and back-end deep neural networks for robust speech recognition

2015

Based on the recently proposed speech pre-processing front-end with deep neural networks (DNNs), we first investigate different feature mapping directly from noisy speech via DNN for robust speech recognition. Next, we propose to jointly train …

Boosting End-to-End Multilingual Phoneme Recognition Through Exploiting Universal Speech Attributes Constraints

2024

We propose a first step toward multilingual end-to-end automatic speech recognition (ASR) by integrating knowledge about speech articulators. The key idea is to leverage a rich set of fundamental units that can be defined "universally" …

Improving non-native mispronunciation detection and enriching diagnostic feedback with DNN-based speech attribute modeling

2016

We propose the use of speech attributes, such as voicing and aspiration, to address two key research issues in computer assisted pronunciation training (CAPT) for L2 learners, namely detecting mispronunciation and providing diagnostic feedback. To …