12 citations · 22 across the 19 of their papers we have counts for
19 papers
DeRA-MOS: Optimizing Text-to-Music Evaluation via Decoupled Listwise Ranking and Modality Alignment
Chien-Chun Wang, Hung-Shin Lee, Hsin-Min Wang +1
Evaluating text-to-music (TTM) systems remains expensive because music impression (MI) and text alignment (TA) scores rely on human mean opinion scores (MOS). Most automatic MOS es…
Robust Generative Audio Quality Assessment: Disentangling Quality from Spurious Correlations
Kuan-Tang Huang, Chien-Chun Wang, Cheng-Yeh Yang +3
The rapid proliferation of AI-Generated Content (AIGC) has necessitated robust metrics for perceptual quality assessment. However, automatic Mean Opinion Score (MOS) prediction mod…
Universal Robust Speech Adaptation for Cross-Domain Speech Recognition and Enhancement
Chien-Chun Wang, Hung-Shin Lee, Hsin-Min Wang +1
Pre-trained models for automatic speech recognition (ASR) and speech enhancement (SE) have exhibited remarkable capabilities under matched noise and channel conditions. However, th…
Efficient Dialect-Aware Modeling and Conditioning for Low-Resource Taiwanese Hakka Speech Processing
An-Ci Peng, Kuan-Tang Huang, Tien-Hong Lo +3
Taiwanese Hakka is a low-resource, endangered language that poses significant challenges for automatic speech recognition (ASR), including high dialectal variability and the presen…
CasNet: Investigating Channel Robustness for Speech Separation
Fan-Lin Wang, Yao-Fei Cheng, Hung-Shin Lee +2
Recording channel mismatch between training and testing conditions has been shown to be a serious problem for speech separation. This situation greatly reduces the separation perfo…
A Training and Inference Strategy Using Noisy and Enhanced Speech as Target for Speech Enhancement without Clean Speech
Li-Wei Chen, Yao-Fei Cheng, Hung-Shin Lee +2
The lack of clean speech is a practical challenge to the development of speech enhancement systems, which means that there is an inevitable mismatch between their training criterio…
Filter-based Discriminative Autoencoders for Children Speech Recognition
Chiang-Lin Tai, Hung-Shin Lee, Yu Tsao +1
Children speech recognition is indispensable but challenging due to the diversity of children's speech. In this paper, we propose a filter-based discriminative autoencoder for acou…
Generation of Speaker Representations Using Heterogeneous Training Batch Assembly
Yu-Huai Peng, Hung-Shin Lee, Pin-Tuan Huang +1
In traditional speaker diarization systems, a well-trained speaker model is a key component to extract representations from consecutive and partially overlapping segments in a long…
Subspace-based Representation and Learning for Phonotactic Spoken Language Recognition
Hung-Shin Lee, Yu Tsao, Shyh-Kang Jeng +1
Phonotactic constraints can be employed to distinguish languages by representing a speech utterance as a multinomial distribution or phone events. In the present study, we propose…
Disentangling the Impacts of Language and Channel Variability on Speech Separation Networks
Fan-Lin Wang, Hung-Shin Lee, Yu Tsao +1
Because the performance of speech separation is excellent for speech in which two speakers completely overlap, research attention has been shifted to dealing with more realistic sc…
Multi-target Extractor and Detector for Unknown-number Speaker Diarization
Chin-Yi Cheng, Hung-Shin Lee, Yu Tsao +1
Strong representations of target speakers can help extract important information about speakers and detect corresponding temporal regions in multi-speaker conversations. In this st…
Speech-enhanced and Noise-aware Networks for Robust Speech Recognition
Hung-Shin Lee, Pin-Yuan Chen, Yao-Fei Cheng +2
Compensation for channel mismatch and noise interference is essential for robust automatic speech recognition. Enhanced speech has been introduced into the multi-condition training…
Chain-based Discriminative Autoencoders for Speech Recognition
Hung-Shin Lee, Pin-Tuan Huang, Yao-Fei Cheng +1
In our previous work, we proposed a discriminative autoencoder (DcAE) for speech recognition. DcAE combines two training schemes into one. First, since DcAE aims to learn encoder-d…
SurpriseNet: Melody Harmonization Conditioning on User-controlled Surprise Contours
Yi-Wei Chen, Hung-Shin Lee, Yen-Hsing Chen +1
The surprisingness of a song is an essential and seemingly subjective factor in determining whether the listener likes it. With the help of information theory, it can be described…
AlloST: Low-resource Speech Translation without Source Transcription
Yao-Fei Cheng, Hung-Shin Lee, Hsin-Min Wang
The end-to-end architecture has made promising progress in speech translation (ST). However, the ST task is still challenging under low-resource conditions. Most ST models have sho…
Relational Data Selection for Data Augmentation of Speaker-dependent Multi-band MelGAN Vocoder
Yi-Chiao Wu, Cheng-Hung Hu, Hung-Shin Lee +5
Nowadays, neural vocoders can generate very high-fidelity speech when a bunch of training data is available. Although a speaker-dependent (SD) vocoder usually outperforms a speaker…
Dual-Path Filter Network: Speaker-Aware Modeling for Speech Separation
Fan-Lin Wang, Yu-Huai Peng, Hung-Shin Lee +1
Speech separation has been extensively studied to deal with the cocktail party problem in recent years. All related approaches can be divided into two categories: time-frequency do…
The Academia Sinica Systems of Voice Conversion for VCC2020
Yu-Huai Peng, Cheng-Hung Hu, Alexander Kang +4
This paper describes the Academia Sinica systems for the two tasks of Voice Conversion Challenge 2020, namely voice conversion within the same language (Task 1) and cross-lingual v…
Melody Harmonization Using Orderless NADE, Chord Balancing, and Blocked Gibbs Sampling
Chung-En Sun, Yi-Wei Chen, Hung-Shin Lee +2
Coherence and interestingness are two criteria for evaluating the performance of melody harmonization, which aims to generate a chord progression from a symbolic melody. In this st…