2 citations · 2 across the 18 of their papers we have counts for
6 papers · 2 filters
Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks
Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang +77
Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spo…
Towards Robust Speech Representation Learning for Thousands of Languages
William Chen, Wangyou Zhang, Yifan Peng +7
Self-supervised learning (SSL) has helped extend speech technologies to more languages by reducing the need for labeled data. However, models are still far from supporting the worl…
On the Evaluation of Speech Foundation Models for Spoken Language Understanding
Siddhant Arora, Ankita Pasad, Chung-Ming Chien +9
The Spoken Language Understanding Evaluation (SLUE) suite of benchmark tasks was recently introduced to address the need for open resources and benchmarking of complex spoken langu…
On the Effects of Heterogeneous Data Sources on Speech-to-Text Foundation Models
Jinchuan Tian, Yifan Peng, William Chen +3
The Open Whisper-style Speech Model (OWSM) series was introduced to achieve full transparency in building advanced speech-to-text (S2T) foundation models. To this end, OWSM models…
YODAS: Youtube-Oriented Dataset for Audio and Speech
Xinjian Li, Shinnosuke Takamichi, Takaaki Saeki +3
In this study, we introduce YODAS (YouTube-Oriented Dataset for Audio and Speech), a large-scale, multilingual dataset comprising currently over 500k hours of speech data in more t…
AugSumm: towards generalizable speech summarization using synthetic labels from large language model
Jee-weon Jung, Roshan Sharma, William Chen +2
Abstractive speech summarization (SSUM) aims to generate human-like summaries from speech. Given variations in information captured and phrasing, recordings can be summarized in mu…