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20242026
most citedWhen LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection

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eess.AS2026

Step-Audio-R1.5 Technical Report

Yuxin Zhang, Xiangyu Tony Zhang, Daijiao Liu +16

Recent advancements in large audio language models have extended Chain-of-Thought (CoT) reasoning into the auditory domain, enabling models to tackle increasingly complex acoustic…

eess.AS2026

StepAudio 2.5 Technical Report

Bin Lin, Bo Zhao, Boyong Wu +98

Unified audio-language modeling has emerged as a prominent trend in modern speech systems, promising to bring the reasoning capabilities of large language models to auditory tasks.…

eess.AS2024

Auto-Landmark: Acoustic Landmark Dataset and Open-Source Toolkit for Landmark Extraction

Xiangyu Zhang, Daijiao Liu, Tianyi Xiao +5

In the speech signal, acoustic landmarks identify times when the acoustic manifestations of the linguistically motivated distinctive features are most salient. Acoustic landmarks h…

eess.AS2024★ 1 cited

When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection

Xiangyu Zhang, Hexin Liu, Kaishuai Xu +4

Depression is a critical concern in global mental health, prompting extensive research into AI-based detection methods. Among various AI technologies, Large Language Models (LLMs)…

eess.AS2024

Speaking in Wavelet Domain: A Simple and Efficient Approach to Speed up Speech Diffusion Model

Xiangyu Zhang, Daijiao Liu, Hexin Liu +5

Recently, Denoising Diffusion Probabilistic Models (DDPMs) have attained leading performances across a diverse range of generative tasks. However, in the field of speech synthesis,…