Research
Generally, my interest is the things that are still interesting 5 years from now.
Specifically, I am currently working on two directions.
(1) Boosting conversational/healthy/educational system with rich spoken language understanding .
With a clear sense of mission, I also work with UCSF to deploy my research outcome into hospitals and K-5 schools across the California!
(2) Real time multi-agents human-robot interaction around multi-modal world.
I am also interested in general AI science/health topics.
Startup Activity
I am co-founding an AI-powered spoken language learning startup, together with my advisor and another genius labmate. Demo will be available shortly.
Please pin me and have a coffee at any time to discuss educational (US, Chinese K12, etc) business collaboration.
Industrial
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Meta AI, CA, USA
Research Intern • May 2022 to Dec. 2022
With: Alexei Baevski, Wei-Ning Hsu, Michael Auli
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Speech and NLP Group, Tencent AI Lab(American) , WA, USA
Research Intern • Dec 2021 to Feb. 2022
With: Chunlei Zhang, Dong Yu
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Speech and NLP Group, Tencent AI Lab(American) , WA, USA
Research Intern • April 2021 to Aug. 2021
With: Chunlei Zhang, Dong Yu
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Selected Publications
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Towards Hierarchical Spoken Language Dysfluency Modeling
Jiachen Lian,
and Gopala
Krishna Anumanchipalli,
2024 EACL (Main Conf/Oral, Long). Hierarchical extension of UDM with monotonicity injection. .
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Unconstrained Dysfluency Modeling for Dysfluent Speech Transcription and Detection
Jiachen Lian,
Carly Feng,
Naasir Farooqi,
Steve Li,
Anshul Kashyap,
Cheol Jun Cho,
Peter Wu,
Robbie Netzorg,
Tingle Li,
and Gopala
Krishna Anumanchipalli,
2023 ASRU (Best Paper Candidate). To be deployed in hospitals and K-5 schools across the California! .
2024 Sevin Rosen Funds Award
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Deep Speech Synthesis from MRI-Based Articulatory Representations
Peter Wu,
Tingle Li,
Yijing Lu,
Yubin Zhang,
Jiachen Lian,
Alan Black,
Louis Goldstein,
Shinji Watanabe,
and Gopala
Krishna Anumanchipalli,
2023 Interspeech.
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AV-data2vec: Self-supervised Learning of Audio-Visual Speech Representations with Contextualized Target Representations
Jiachen Lian,
Alexei Baevski,
Wei-Ning Hsu,
and Michael Auli,
2023 ASRU.
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Articulatory Representation Learning Via Joint Factor Analysis and Neural Matrix Factorization
Jiachen Lian,
Alan W Black,
Yijing Lu,
Louis Goldstein,
Shinji Watanabe,
and Gopala Krishna Anumanchipalli,
2023 ICASSP.
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UTTS: Unsupervised TTS with Conditional Disentangled Sequential Variational Auto-encoder
Jiachen Lian*,
Chunlei Zhang*,
Gopala Krishna Anumanchipalli, and
Dong Yu.
IEEE/ACM Transactions on Audio, Speech, and Language Processing . [Demo]
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Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition
Jiachen Lian,
Alan W Black,
Louis Goldstein, and
Gopala Krishna Anumanchipalli.
2022 Interspeech. [code]
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Towards Improved Voice Conversion with Conditional DSVAE
Jiachen Lian*,
Chunlei Zhang*,
Gopala Krishna Anumanchipalli, and
Dong Yu.
2022 Interspeech. [Demo]
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Robust Disentangled Variational Speech Representation Learning for Zero-shot Voice Conversion
Jiachen Lian,
Chunlei Zhang, and
Dong Yu.
2022 ICASSP. [Demo]
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Masked Proxy Loss For Text-Independent Speaker Verification
Jiachen Lian,
Aiswarya Vinod Kumar,
Hira Dhamyal,
Bhiksha Raj, and
Rita Singh.
2021 Interspeech (ISCA Student Travel Grant)
. [Code]
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Detection and Evaluation of Human and Machine Generated Speech in Spoofing Attacks on Automatic Speaker Verification Systems
Yang Gao,
Jiachen Lian,
Bhiksha Raj, and
Rita Singh.
2021 SLT.
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Education
UC Berkeley, U.S.
Ph.D. in EECS • Aug. 2021 to Present
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Carnegie Mellon University, U.S.
M.S. in ECE • Sept.2019 to Dec. 2020
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Zhejiang University, China
B.Eng. in EE • Aug. 2015 to June 2019
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