Patrick Lumban Tobing

About Patrick Lumban Tobing

Patrick Lumban Tobing, With an exceptional h-index of 12 and a recent h-index of 12 (since 2020), a distinguished researcher at Nagoya University, specializes in the field of Speech Synthesis, Voice Conversion, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Mapache: Masked Parallel Transformer for Advanced Speech Editing and Synthesis

Cross-lingual prosody transfer for expressive machine dubbing

Expressive machine dubbing through phrase-level cross-lingual prosody transfer

A Cyclical Approach to Synthetic and Natural Speech Mismatch Refinement of Neural Post-filter for Low-cost Text-to-speech System

Direct noisy speech modeling for noisy-to-noisy voice conversion

Noisy-to-noisy voice conversion framework with denoising model

crank: An open-source software for nonparallel voice conversion based on vector-quantized variational autoencoder

Low-latency real-time non-parallel voice conversion based on cyclic variational autoencoder and multiband WaveRNN with data-driven linear prediction

Patrick Lumban Tobing Information

University

Position

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Citations(all)

442

Citations(since 2020)

409

Cited By

223

hIndex(all)

12

hIndex(since 2020)

12

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Patrick Lumban Tobing Skills & Research Interests

Speech Synthesis

Voice Conversion

Machine Learning

Top articles of Patrick Lumban Tobing

Mapache: Masked Parallel Transformer for Advanced Speech Editing and Synthesis

2024

Cross-lingual prosody transfer for expressive machine dubbing

arXiv preprint arXiv:2306.11658

2023/6/20

Duo Wang
Duo Wang

H-Index: 1

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Expressive machine dubbing through phrase-level cross-lingual prosody transfer

arXiv preprint arXiv:2306.11662

2023/6/20

Duo Wang
Duo Wang

H-Index: 1

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

A Cyclical Approach to Synthetic and Natural Speech Mismatch Refinement of Neural Post-filter for Low-cost Text-to-speech System

APSIPA Transactions on Signal and Information Processing

2022/7/13

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Tomoki Toda
Tomoki Toda

H-Index: 34

Direct noisy speech modeling for noisy-to-noisy voice conversion

2022/5/23

Noisy-to-noisy voice conversion framework with denoising model

2021/12/14

crank: An open-source software for nonparallel voice conversion based on vector-quantized variational autoencoder

2021/6/6

Low-latency real-time non-parallel voice conversion based on cyclic variational autoencoder and multiband WaveRNN with data-driven linear prediction

arXiv preprint arXiv:2105.09858

2021/5/20

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Tomoki Toda
Tomoki Toda

H-Index: 34

High-fidelity and low-latency universal neural vocoder based on multiband WaveRNN with data-driven linear prediction for discrete waveform modeling

arXiv preprint arXiv:2105.09856

2021/5/20

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Tomoki Toda
Tomoki Toda

H-Index: 34

Quasi-periodic WaveNet: An autoregressive raw waveform generative model with pitch-dependent dilated convolution neural network

IEEE/ACM Transactions on Audio, Speech, and Language Processing

2021/2/23

Semi-supervised enhancement and suppression of self-produced speech using correspondence between air-and body-conducted signals

2021/1/18

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Tomoki Toda
Tomoki Toda

H-Index: 34

Cross-lingual voice conversion using a cyclic variational auto-encoder and a WaveNet vocoder

2020/12/7

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Kazuya Takeda
Kazuya Takeda

H-Index: 27

Tomoki Toda
Tomoki Toda

H-Index: 34

The NU voice conversion system for the Voice Conversion Challenge 2020: On the effectiveness of sequence-to-sequence models and autoregressive neural vocoders

arXiv preprint arXiv:2010.04446

2020/10/9

Baseline system of Voice Conversion Challenge 2020 with cyclic variational autoencoder and Parallel WaveGAN

arXiv preprint arXiv:2010.04429

2020/10/9

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Tomoki Toda
Tomoki Toda

H-Index: 34

A cyclical post-filtering approach to mismatch refinement of neural vocoder for text-to-speech systems

arXiv preprint arXiv:2005.08659

2020/5/18

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Tomoki Toda
Tomoki Toda

H-Index: 34

Efficient shallow wavenet vocoder using multiple samples output based on laplacian distribution and linear prediction

2020/5/4

Non-parallel voice conversion system with WaveNet vocoder and collapsed speech suppression

IEEE Access

2020/3/30

Cross-Lingual Voice Conversion using Cyclic Variational Auto-encoder

IEICE Technical Report; IEICE Tech. Rep.

2020/2/24

Patrick Lumban Tobing
Patrick Lumban Tobing

H-Index: 9

Kazuya Takeda
Kazuya Takeda

H-Index: 27

Tomoki Toda
Tomoki Toda

H-Index: 34

An evaluation of voice conversion with neural network spectral mapping models and WaveNet vocoder

APSIPA Transactions on Signal and Information Processing

2020/1

Cyclic Spectral Modeling for Unsupervised Unit Discovery into Voice Conversion with Excitation and Waveform Modeling.

2020

See List of Professors in Patrick Lumban Tobing University(Nagoya University)

Co-Authors

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