1 citations · 1 across the 4 of their papers we have counts for
4 papers
Unsupervised Discovery of Structured Acoustic Tokens with Applications to Spoken Term Detection
Cheng-Tao Chung, Lin-Shan Lee
In this paper, we compare two paradigms for unsupervised discovery of structured acoustic tokens directly from speech corpora without any human annotation. The Multigranular Paradi…
Unsupervised Iterative Deep Learning of Speech Features and Acoustic Tokens with Applications to Spoken Term Detection
Cheng-Tao Chung, Cheng-Yu Tsai, Chia-Hsiang Liu +1
In this paper we aim to automatically discover high quality frame-level speech features and acoustic tokens directly from unlabeled speech data. A Multi-granular Acoustic Tokenizer…
Personalized Acoustic Modeling by Weakly Supervised Multi-Task Deep Learning using Acoustic Tokens Discovered from Unlabeled Data
Cheng-Kuan Wei, Cheng-Tao Chung, Hung-Yi Lee +1
It is well known that recognizers personalized to each user are much more effective than user-independent recognizers. With the popularity of smartphones today, although it is not…
A Multi-layered Acoustic Tokenizing Deep Neural Network (MAT-DNN) for Unsupervised Discovery of Linguistic Units and Generation of High Quality Features
Cheng-Tao Chung, Cheng-Yu Tsai, Hsiang-Hung Lu +5
This paper summarizes the work done by the authors for the Zero Resource Speech Challenge organized in the technical program of Interspeech 2015. The goal of the challenge is to di…