53 citations · 205 across the 57 of their papers we have counts for
10 papers · 1 filter
Joint Beam Search Integrating CTC, Attention, and Transducer Decoders
Yui Sudo, Muhammad Shakeel, Yosuke Fukumoto +4
End-to-end automatic speech recognition (E2E-ASR) can be classified by its decoder architectures, such as connectionist temporal classification (CTC), recurrent neural network tran…
A Large-Scale Evaluation of Speech Foundation Models
Shu-wen Yang, Heng-Jui Chang, Zili Huang +18
The foundation model paradigm leverages a shared foundation model to achieve state-of-the-art (SOTA) performance for various tasks, requiring minimal downstream-specific modeling a…
Dynamic-SUPERB: Towards A Dynamic, Collaborative, and Comprehensive Instruction-Tuning Benchmark for Speech
Chien-yu Huang, Ke-Han Lu, Shih-Heng Wang +12
Text language models have shown remarkable zero-shot capability in generalizing to unseen tasks when provided with well-formulated instructions. However, existing studies in speech…
SingAug: Data Augmentation for Singing Voice Synthesis with Cycle-consistent Training Strategy
Shuai Guo, Jiatong Shi, Tao Qian +2
Deep learning based singing voice synthesis (SVS) systems have been demonstrated to flexibly generate singing with better qualities, compared to conventional statistical parametric…
Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity
Peter Wu, Jiatong Shi, Yifan Zhong +2
Speech processing systems currently do not support the vast majority of languages, in part due to the lack of data in low-resource languages. Cross-lingual transfer offers a compel…
Leveraging End-to-End ASR for Endangered Language Documentation: An Empirical Study on Yoloxóchitl Mixtec
Jiatong Shi, Jonathan D. Amith, Rey Castillo García +3
"Transcription bottlenecks", created by a shortage of effective human transcribers are one of the main challenges to endangered language (EL) documentation. Automatic speech recogn…
Understanding the Tradeoffs in Client-side Privacy for Downstream Speech Tasks
Peter Wu, Paul Pu Liang, Jiatong Shi +3
As users increasingly rely on cloud-based computing services, it is important to ensure that uploaded speech data remains private. Existing solutions rely either on server-side met…
Recent Developments on ESPnet Toolkit Boosted by Conformer
Pengcheng Guo, Florian Boyer, Xuankai Chang +12
In this study, we present recent developments on ESPnet: End-to-End Speech Processing toolkit, which mainly involves a recently proposed architecture called Conformer, Convolution-…
Sequence-to-sequence Singing Voice Synthesis with Perceptual Entropy Loss
Jiatong Shi, Shuai Guo, Nan Huo +2
The neural network (NN) based singing voice synthesis (SVS) systems require sufficient data to train well and are prone to over-fitting due to data scarcity. However, we often enco…
Context-aware Goodness of Pronunciation for Computer-Assisted Pronunciation Training
Jiatong Shi, Nan Huo, Qin Jin
Mispronunciation detection is an essential component of the Computer-Assisted Pronunciation Training (CAPT) systems. State-of-the-art mispronunciation detection models use Deep Neu…