6 papers
Hybrid Neural-LLM Pipeline for Morphological Glossing in Endangered Language Documentation: A Case Study of Jungar Tuvan
Siyu Liang, Talant Mawkanuli, Gina-Anne Levow
Interlinear glossed text (IGT) creation remains a major bottleneck in linguistic documentation and fieldwork, particularly for low-resource morphologically rich languages. We prese…
A Sociophonetic Analysis of Racial Bias in Commercial ASR Systems Using the Pacific Northwest English Corpus
Michael Scott, Siyu Liang, Alicia Wassink +1
This paper presents a systematic evaluation of racial bias in four major commercial automatic speech recognition (ASR) systems using the Pacific Northwest English (PNWE) corpus. We…
The Limits of Data Scaling: Sub-token Utilization and Acoustic Saturation in Multilingual ASR
Siyu Liang, Nicolas Ballier, Gina-Anne Levow +1
How much audio is needed to fully observe a multilingual ASR model's learned sub-token inventory across languages, and does data disparity in multilingual pre-training affect how t…
Beyond WER: Probing Whisper's Sub-token Decoder Across Diverse Language Resource Levels
Siyu Liang, Nicolas Ballier, Gina-Anne Levow +1
While large multilingual automatic speech recognition (ASR) models achieve remarkable performance, the internal mechanisms of the end-to-end pipeline, particularly concerning fairn…
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages
Siyu Liang, Gina-Anne Levow
Automatic Speech Recognition (ASR) has reached impressive accuracy for high-resource languages, yet its utility in linguistic fieldwork remains limited. Recordings collected in fie…
TEII: Think, Explain, Interact and Iterate with Large Language Models to Solve Cross-lingual Emotion Detection
Long Cheng, Qihao Shao, Christine Zhao +2
Cross-lingual emotion detection allows us to analyze global trends, public opinion, and social phenomena at scale. We participated in the Explainability of Cross-lingual Emotion De…