Sung-Feng Huang

Orcid: 0000-0002-9720-811X

According to our database1, Sung-Feng Huang authored at least 18 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Personalized Lightweight Text-to-Speech: Voice Cloning with Adaptive Structured Pruning.
Proceedings of the IEEE International Conference on Acoustics, 2023

Maximizing Data Efficiency for Cross-Lingual TTS Adaptation by Self-Supervised Representation Mixing and Embedding Initialization.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022
Learning Phone Recognition From Unpaired Audio and Phone Sequences Based on Generative Adversarial Network.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

Meta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech.
IEEE ACM Trans. Audio Speech Lang. Process., 2022

Few Shot Cross-Lingual TTS Using Transferable Phoneme Embedding.
Proceedings of the Interspeech 2022, 2022

2021
Meta-TTS: Meta-Learning for Few-Shot Speaker Adaptive Text-to-Speech.
CoRR, 2021

SpeechNet: A Universal Modularized Model for Speech Processing Tasks.
CoRR, 2021

Non-autoregressive Mandarin-English Code-switching Speech Recognition with Pinyin Mask-CTC and Word Embedding Regularization.
CoRR, 2021

Stabilizing Label Assignment for Speech Separation by Self-Supervised Pre-Training.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

Non-Autoregressive Mandarin-English Code-Switching Speech Recognition.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

2020
Self-supervised Pre-training Reduces Label Permutation Instability of Speech Separation.
CoRR, 2020

Pretrained Language Model Embryology: The Birth of ALBERT.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Audio Word2vec: Sequence-to-Sequence Autoencoding for Unsupervised Learning of Audio Segmentation and Representation.
IEEE ACM Trans. Audio Speech Lang. Process., 2019

From Semi-supervised to Almost-unsupervised Speech Recognition with Very-low Resource by Jointly Learning Phonetic Structures from Audio and Text Embeddings.
CoRR, 2019

2018
Improved Audio Embeddings by Adjacency-Based Clustering with Applications in Spoken Term Detection.
CoRR, 2018

Almost-unsupervised Speech Recognition with Close-to-zero Resource Based on Phonetic Structures Learned from Very Small Unpaired Speech and Text Data.
CoRR, 2018

Towards Unsupervised Automatic Speech Recognition Trained by Unaligned Speech and Text only.
CoRR, 2018

Phonetic-and-Semantic Embedding of Spoken words with Applications in Spoken Content Retrieval.
Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018


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