Papers by Tongzhou Chen

3 papers
Aerial Vision-and-Dialog Navigation (2023.findings-acl)

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Challenge: Aerial visionand-dialling navigation (AVDN) is a new approach to autonomous drones that can converse with humans and follow natural language commands to complete tasks.
Approach: They propose to use Aerial Visionand-Dialog Navigation (AVDN) to navigate a drone via natural language conversation by collecting a dataset of over 3k recorded navigation trajectories with asynchronous human-human dialogs between commanders and followers.
Outcome: The proposed system can converse with humans and follow natural language commands to fly to the expected destination.
LegoSLM: Connecting LLM with Speech Encoder using CTC Posteriors (2025.findings-emnlp)

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Challenge: Recent studies show that pre-trained speech encoders and large language models can perform suboptimal performance on a range of spoken language processing tasks.
Approach: They propose to combine large-scale pre-trained speech encoders and large-language models for better performance on automatic speech recognition tasks.
Outcome: The proposed model can get an average of 49% WER reduction over the baseline model on 8 MLS testsets.
Data Quality Issues in Multilingual Speech Datasets: The Need for Sociolinguistic Awareness and Proactive Language Planning (2025.acl-long)

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Challenge: Despite their growing importance, the quality of these datasets remains under-researched.
Approach: They propose guidelines and recommendations to address quality issues in future dataset development . they find that macro-level issues are more prevalent in less institutionalized, often under-resourced languages .
Outcome: The results highlight the need for proactive language planning and enhanced data quality control in the process of automatic speech recognition dataset creation.

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