activity
20232026
most citedSpeechPrompt: Prompting Speech Language Models for Speech Processing Tasks

8 citations · 20 across the 23 of their papers we have counts for

collaborators
Showing 2026Show all

11 papers · 1 filter

cs.CL2026

D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones

Cheng-Kuang Chang, Alexander H. Liu, Brian Kingsbury +5

Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-SLMs) in general capabilities.…

eess.AS2026

MP-Bench: Evaluating Voice Agents as a Multiparty Conversation Participant

Yi-Jen Shih, Shih-Yun Shan Kuan, Guan-Ting Lin +7

Conversational voice agents have advanced significantly, offering increasingly natural human-machine interactions through both cascaded and end-to-end architectures. However, while…

eess.AS2026

AudioICL-Bench: A Benchmark for Large Audio Language Model In-Context Learning

Jia-Hung Chen, Yi-Cheng Lin, Kai-Wei Chang +2

In-context learning (ICL) promises training-free adaptation for audio, where labeling every new condition is costly. Yet existing audio ICL studies largely measure Task Recognition…

eess.AS2026

Unsupervised Speech Recognition at the Syllable Level

Liming Wang, Kai-Wei Chang, Kunio Kashino +3

Training speech recognizers with unpaired speech and text -- known as unsupervised speech recognition (UASR) -- is a crucial step toward extending ASR to low-resource languages in…

cs.LG2026

Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks

Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1

With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…

cs.CL2026

Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering

Cheng-Kuang Chang, Kai-Wei Chang, Alexander H. Liu +1

Full-duplex spoken language models (FD-SLMs) enable seamless speech interaction by allowing models to listen and speak simultaneously, yet the internal mechanism by which they coor…

eess.AS2026

RRP-Voice: A Longitudinal Dataset and Benchmark for Recurrent Respiratory Papillomatosis Detection

Wenze Ren, Ke-Han Lu, Kai-Wei Chang +8

Deep learning has advanced pathological voice detection rapidly, yet rare laryngeal diseases remain underexplored due to data scarcity. Recurrent Respiratory Papillomatosis (RRP) e…

cs.CL2026

TiCo: Time-Controllable Spoken Dialogue Model

Kai-Wei Chang, Wei-Chih Chen, En-Pei Hu +2

We introduce TiCo, a time-controllable spoken dialogue model (SDM) that follows time-constrained instructions (e.g., "Please generate a response lasting about 15 seconds") and gene…

cs.CL2026

TaigiSpeech: A Low-Resource Real-World Speech Intent Dataset and Preliminary Results with Scalable Data Mining In-the-Wild

Kai-Wei Chang, Yi-Cheng Lin, Huang-Cheng Chou +9

Speech technologies have advanced rapidly and serve diverse populations worldwide. However, many languages remain underrepresented due to limited resources. In this paper, we intro…

eess.AS2026

AQAScore: Evaluating Semantic Alignment in Text-to-Audio Generation via Audio Question Answering

Chun-Yi Kuan, Kai-Wei Chang, Hung-yi Lee

Although text-to-audio generation has made remarkable progress in realism and diversity, the development of evaluation metrics has not kept pace. Widely-adopted approaches, typical…

cs.CL2026

On the Fallacy of Global Token Perplexity in Spoken Language Model Evaluation

Chan-Jan Hsu, Liang-Hsuan Tseng, Yi-Cheng Lin +5

Generative spoken language models pretrained on large-scale raw audio can continue a speech prompt with appropriate content while preserving attributes like speaker and emotion, se…