Julian Chan - researchr alias

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Viewing Publication 1 - 11 from 11

2025

Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised DisentanglementXueyao Zhang, Xiaohui Zhang, Kainan Peng, Zhenyu Tang, Vimal Manohar, Yingru Liu, Jeff Hwang, Dangna Li, Yuhao Wang, Julian Chan, Yuan Huang, Zhizheng Wu 0001, Mingbo Ma. iclr 2025: [doi]

2021

Deep Shallow Fusion for RNN-T PersonalizationDuc Le, Gil Keren, Julian Chan, Jay Mahadeokar, Christian Fuegen, Michael L. Seltzer. slt 2021: 251-257 [doi]

Contextualized Streaming End-to-End Speech Recognition with Trie-Based Deep Biasing and Shallow FusionDuc Le, Mahaveer Jain, Gil Keren, Suyoun Kim, Yangyang Shi, Jay Mahadeokar, Julian Chan, Yuan Shangguan, Christian Fuegen, Ozlem Kalinli, Yatharth Saraf, Michael L. Seltzer. interspeech 2021: 1772-1776 [doi]

Emformer: Efficient Memory Transformer Based Acoustic Model for Low Latency Streaming Speech RecognitionYangyang Shi, Yongqiang Wang, Chunyang Wu, Ching-feng Yeh, Julian Chan, Frank Zhang 0001, Duc Le, Mike Seltzer. icassp 2021: 6783-6787 [doi]

Dynamic Encoder Transducer: A Flexible Solution for Trading Off Accuracy for LatencyYangyang Shi, Varun Nagaraja, Chunyang Wu, Jay Mahadeokar, Duc Le, Rohit Prabhavalkar, Alex Xiao, Ching-feng Yeh, Julian Chan, Christian Fuegen, Ozlem Kalinli, Michael L. Seltzer. interspeech 2021: 2042-2046 [doi]

Transformer in Action: A Comparative Study of Transformer-Based Acoustic Models for Large Scale Speech Recognition ApplicationsYongqiang Wang, Yangyang Shi, Frank Zhang 0001, Chunyang Wu, Julian Chan, Ching-feng Yeh, Alex Xiao. icassp 2021: 6778-6782 [doi]

Streaming Attention-Based Models with Augmented Memory for End-To-End Speech RecognitionChing-feng Yeh, Yongqiang Wang, Yangyang Shi, Chunyang Wu, Frank Zhang 0001, Julian Chan, Michael L. Seltzer. slt 2021: 8-14 [doi]

Benchmarking LF-MMI, CTC And RNN-T Criteria For Streaming ASRXiaohui Zhang, Frank Zhang 0001, Chunxi Liu, Kjell Schubert, Julian Chan, Pradyot Prakash, Jun Liu, Ching-feng Yeh, Fuchun Peng, Yatharth Saraf, Geoffrey Zweig. slt 2021: 46-51 [doi]

On Lattice-Free Boosted MMI Training of HMM and CTC-Based Full-Context ASR ModelsXiaohui Zhang, Vimal Manohar, David Zhang, Frank Zhang 0001, Yangyang Shi, Nayan Singhal, Julian Chan, Fuchun Peng, Yatharth Saraf, Mike Seltzer. asru 2021: 1026-1033 [doi]

2014

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