activity
20162022
most citedMeta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech

54 citations · 148 across the 12 of their papers we have counts for

collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2021★ 6 cited

SpeechNet: A Universal Modularized Model for Speech Processing Tasks

Yi-Chen Chen, Po-Han Chi, Shu-wen Yang +7

There is a wide variety of speech processing tasks ranging from extracting content information from speech signals to generating speech signals. For different tasks, model networks…

cs.CL2021★ 53 cited

SUPERB: Speech processing Universal PERformance Benchmark

Shu-wen Yang, Po-Han Chi, Yung-Sung Chuang +17

Self-supervised learning (SSL) has proven vital for advancing research in natural language processing (NLP) and computer vision (CV). The paradigm pretrains a shared model on large…

cs.CL2020★ 5 cited

Contextualizing ASR Lattice Rescoring with Hybrid Pointer Network Language Model

Da-Rong Liu, Chunxi Liu, Frank Zhang +3

Videos uploaded on social media are often accompanied with textual descriptions. In building automatic speech recognition (ASR) systems for videos, we can exploit the contextual in…

cs.CL2019★ 15 cited

Completely Unsupervised Speech Recognition By A Generative Adversarial Network Harmonized With Iteratively Refined Hidden Markov Models

Kuan-Yu Chen, Che-Ping Tsai, Da-Rong Liu +2

Producing a large annotated speech corpus for training ASR systems remains difficult for more than 95% of languages all over the world which are low-resourced, but collecting a rel…

cs.CL2018★ 2 cited

Completely Unsupervised Phoneme Recognition by Adversarially Learning Mapping Relationships from Audio Embeddings

Da-Rong Liu, Kuan-Yu Chen, Hung-Yi Lee +1

Unsupervised discovery of acoustic tokens from audio corpora without annotation and learning vector representations for these tokens have been widely studied. Although these techni…

cs.CL2016★ 4 cited

Attention-based Memory Selection Recurrent Network for Language Modeling

Da-Rong Liu, Shun-Po Chuang, Hung-yi Lee

Recurrent neural networks (RNNs) have achieved great success in language modeling. However, since the RNNs have fixed size of memory, their memory cannot store all the information…