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Yi-Cheng Lin

8 accepted papers

2026

Do You Hear What I Mean? Quantifying the Instruction-Perception Gap in Instruction-Guided Expressive Text-To-Speech Systems

ICASSP 2026oral

Instruction-guided text-to-speech (ITTS) enables users to control speech generation through natural language prompts, offering a more intuitive interface than traditional TTS. However, the alignment between user style instructions and listener perception remains largely unexplored. This work first p…

Cited by 1SourcePDFScholar
2026

WaveSP-Net: Learnable Wavelet-Domain Sparse Prompt Tuning for Speech Deepfake Detection

ICASSP 2026poster

Modern front-end design for speech deepfake detection relies on full fine-tuning of large pre-trained models like XLSR. However, this approach is not parameter-efficient and may lead to suboptimal generalization to realistic, in-the-wild data types. To address these limitations, we introduce a new f…

Cited by 0SourcePDFScholar
2025

Creativity in LLM-based Multi-Agent Systems: A Survey

EMNLP 2025

Large language model (LLM)-driven multi-agent systems (MAS) are transforming how humans and AIs collaboratively generate ideas and artifacts. While existing surveys provide comprehensive overviews of MAS infrastructures, they largely overlook the dimension of creativity , including how novel outputs

2025

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

ICLR 2025poster

Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spoken language model that comprehends a wide range of natural language instructions is critical for bridging communication…

2025

Improving Speech Emotion Recognition in Under-Resourced Languages via Speech-to-Speech Translation with Bootstrapping Data Selection

ICASSP 2025accepted

Speech Emotion Recognition (SER) is a crucial component in developing general-purpose AI agents capable of natural human-computer interaction. However, building robust multilingual SER systems remains challenging due to the scarcity of labeled data in languages other than English and Chinese. In thi…

Cited by 0SourceScholar
2025

Leveraging Joint Spectral and Spatial Learning with MAMBA for Multichannel Speech Enhancement

ICASSP 2025accepted

In multichannel speech enhancement, effectively capturing spatial and spectral information across different microphones is crucial for noise reduction. Traditional methods, such as CNN or LSTM, attempt to model the temporal dynamics of full-band and sub-band spectral and spatial features. However, t…

Cited by 0SourceScholar
2024

Codec-SUPERB: An In-Depth Analysis of Sound Codec Models

ACL 2024findings

The sound codec’s dual roles in minimizing data transmission latency and serving as tokenizers underscore its critical importance.Recent years have witnessed significant developments in codec models.The ideal sound codec should preserve content, paralinguistics, speakers, and audio information.Howev…