Search Results for author: Li-Wei Chen

Found 17 papers, 10 papers with code

A unified one-shot prosody and speaker conversion system with self-supervised discrete speech units

1 code implementation12 Nov 2022 Li-Wei Chen, Shinji Watanabe, Alexander Rudnicky

To address these issues, we devise a cascaded modular system leveraging self-supervised discrete speech units as language representation.

Voice Conversion

A Teacher-student Framework for Unsupervised Speech Enhancement Using Noise Remixing Training and Two-stage Inference

1 code implementation27 Oct 2022 Li-Wei Chen, Yao-Fei Cheng, Hung-Shin Lee, Yu Tsao, Hsin-Min Wang

The lack of clean speech is a practical challenge to the development of speech enhancement systems, which means that the training of neural network models must be done in an unsupervised manner, and there is an inevitable mismatch between their training criterion and evaluation metric.

Speech Enhancement

Learning Similarity Metrics for Volumetric Simulations with Multiscale CNNs

1 code implementation8 Feb 2022 Georg Kohl, Li-Wei Chen, Nils Thuerey

Simulations that produce three-dimensional data are ubiquitous in science, ranging from fluid flows to plasma physics.

Fine-grained style control in Transformer-based Text-to-speech Synthesis

1 code implementation12 Oct 2021 Li-Wei Chen, Alexander Rudnicky

In this paper, we present a novel architecture to realize fine-grained style control on the transformer-based text-to-speech synthesis (TransformerTTS).

Inductive Bias Speech Synthesis +1

Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils

1 code implementation5 Sep 2021 Li-Wei Chen, Nils Thuerey

The present study investigates the accurate inference of Reynolds-averaged Navier-Stokes solutions for the compressible flow over aerofoils in two dimensions with a deep neural network.

Friction

Spectral Analysis for Semantic Segmentation with Applications on Feature Truncation and Weak Annotation

no code implementations28 Dec 2020 Li-Wei Chen, Wei-Chen Chiu, Chin-Tien Wu

We propose a spectral analysis to investigate the correlations among the resolution of the down sampled grid, the loss function and the accuracy of the SSNNs.

Network Pruning Semantic Segmentation

Numerical investigation of minimum drag profiles in laminar flow using deep learning surrogates

1 code implementation29 Sep 2020 Li-Wei Chen, Berkay Alp Cakal, Xiangyu Hu, Nils Thuerey

In the present study, U-net based deep neural network (DNN) models are trained with high-fidelity datasets to infer flow fields, and then employed as surrogate models to carry out the shape optimisation problem, i. e. to find a drag minimal profile with a fixed cross-section area subjected to a two-dimensional steady laminar flow.

Fluid Dynamics

Encoding Implicit Relation Requirements for Relation Extraction: A Joint Inference Approach

no code implementations9 Nov 2018 Li-Wei Chen, Yansong Feng, Songfang Huang, Bingfeng Luo, Dongyan Zhao

Relation extraction is the task of identifying predefined relationship between entities, and plays an essential role in information extraction, knowledge base construction, question answering and so on.

Question Answering Relation Extraction

Generative Adversarial Networks for Unpaired Voice Transformation on Impaired Speech

1 code implementation30 Oct 2018 Li-Wei Chen, Hung-Yi Lee, Yu Tsao

This paper focuses on using voice conversion (VC) to improve the speech intelligibility of surgical patients who have had parts of their articulators removed.

Voice Conversion

Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model

1 code implementation EMNLP 2018 Kun Xu, Lingfei Wu, Zhiguo Wang, Mo Yu, Li-Wei Chen, Vadim Sheinin

Existing neural semantic parsers mainly utilize a sequence encoder, i. e., a sequential LSTM, to extract word order features while neglecting other valuable syntactic information such as dependency graph or constituent trees.

Graph-to-Sequence Semantic Parsing

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