Papers by Shenran Wang
Developing multilingual speech synthesis system for Ojibwe, Mi’kmaq, and Maliseet (2025.naacl-short)
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| Challenge: | In general, speech synthesis for Indigenous languages is underdeveloped compared to the majority of languages. |
| Approach: | They propose to train a multilingual model on three typologically similar languages to improve performance over monolingual models. |
| Outcome: | The proposed model can train on three similar languages with high performance and is highly competitive with self-attention architectures with higher memory efficiency. |
Exploring Cross-Lingual Voice Conversion Methods for Anonymizing Low-Resource Text-to-Speech (2026.eacl-short)
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| Challenge: | a growing number of speech synthesis systems clone a person's voice, a new study finds . a variety of voice conversion techniques can mask speaker identities in low-resource text-to-speech systems. |
| Approach: | They compare voice conversion techniques to mask speaker identities in text-to-speech systems . they build and evaluate speaker-anonymized systems for two Canadian Indigenous languages . |
| Outcome: | The proposed methods are compared with other approaches for using voice conversion to mask speaker identities in low-resource text-to-speech systems. |
Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures (2026.findings-acl)
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| Challenge: | In-context learning is an emergent ability from pretrained Large Language Models (LLMs). |
| Approach: | They perform in-depth evaluations of in-context learning on transformers and hybrid large language models using behavioral probing and intervention-based methods. |
| Outcome: | The proposed model performs well on state-of-the-art transformer, state-space, and hybrid large language models. |