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20242026
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cs.CL2026

Bagpiper: Solving Open-Ended Audio Tasks via Rich Captions

Jinchuan Tian, Haoran Wang, Bo-Hao Su +14

Current audio foundation models typically rely on rigid, task-specific supervision (e.g., speech recognition), addressing isolated factors of audio rather than the whole. In contra…

cs.CL2025

CS-FLEURS: A Massively Multilingual and Code-Switched Speech Dataset

Brian Yan, Injy Hamed, Shuichiro Shimizu +24

We present CS-FLEURS, a new dataset for developing and evaluating code-switched speech recognition and translation systems beyond high-resourced languages. CS-FLEURS consists of 4…

cs.CL2025

OpusLM: A Family of Open Unified Speech Language Models

Jinchuan Tian, William Chen, Yifan Peng +9

This paper presents Open Unified Speech Language Models (OpusLMs), a family of open foundational speech language models (SpeechLMs) up to 7B. Initialized from decoder-only text lan…

cs.CL2025

OWSM v4: Improving Open Whisper-Style Speech Models via Data Scaling and Cleaning

Yifan Peng, Shakeel Muhammad, Yui Sudo +4

The Open Whisper-style Speech Models (OWSM) project has developed a series of fully open speech foundation models using academic-scale resources, but their training data remains in…

cs.CL2025

ESPnet-SDS: Unified Toolkit and Demo for Spoken Dialogue Systems

Siddhant Arora, Yifan Peng, Jiatong Shi +9

Advancements in audio foundation models (FMs) have fueled interest in end-to-end (E2E) spoken dialogue systems, but different web interfaces for each system makes it challenging to…

cs.CL2025

Proactive Privacy Amnesia for Large Language Models: Safeguarding PII with Negligible Impact on Model Utility

Martin Kuo, Jingyang Zhang, Jianyi Zhang +9

With the rise of large language models (LLMs), increasing research has recognized their risk of leaking personally identifiable information (PII) under malicious attacks. Although…