28 citations · 109 across the 36 of their papers we have counts for
5 papers · 1 filter
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…
Personalized word representations Carrying Personalized Semantics Learned from Social Network Posts
Zih-Wei Lin, Tzu-Wei Sung, Hung-Yi Lee +1
Distributed word representations have been shown to be very useful in various natural language processing (NLP) application tasks. These word vectors learned from huge corpora very…
Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification
Bo-Ru Lu, Frank Shyu, Yun-Nung Chen +2
Connectionist temporal classification (CTC) is a powerful approach for sequence-to-sequence learning, and has been popularly used in speech recognition. The central ideas of CTC in…
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…