Papers by Xiangying Chen

2 papers
S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models (2026.acl-long)

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Challenge: Existing benchmarks rely heavily on text-based evaluation and largely ignore paralinguistic cues such as prosody, emotion, and speaker traits.
Approach: They propose a speech-native benchmark for evaluating instruction-following S2S models with explicit assessment of both semantic understanding and paralinguistic expression.
Outcome: The proposed system enables more natural, robust, and human-aligned speech agents.
Task-oriented Dialogue System for Automatic Diagnosis (P18-2)

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Challenge: Existing methods to identify phenotypes using electronic health records (EHRs) are expensive and difficult to transfer models from one disease to another.
Approach: They propose a task-oriented dialogue system framework to make diagnosis for patients automatically, which can converse with patients to collect additional symptoms beyond their self-reports.
Outcome: The proposed system can collect additional symptoms from conversation and improve disease identification accuracy.

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