47 citations · 115 across the 22 of their papers we have counts for
8 papers · 1 filter
MeanFlow-TSE: One-Step Generative Target Speaker Extraction with Mean Flow
Riki Shimizu, Xilin Jiang, Nima Mesgarani
Target speaker extraction (TSE) aims to isolate a desired speaker's voice from a multi-speaker mixture using auxiliary information such as a reference utterance. Although recent ad…
SightSound-R1: Cross-Modal Reasoning Distillation from Vision to Audio Language Models
Qiaolin Wang, Xilin Jiang, Linyang He +2
While large audio-language models (LALMs) have demonstrated state-of-the-art audio understanding, their reasoning capability in complex soundscapes still falls behind large vision-…
Layer-wise Minimal Pair Probing Reveals Contextual Grammatical-Conceptual Hierarchy in Speech Representations
Linyang He, Qiaolin Wang, Xilin Jiang +1
Transformer-based speech language models (SLMs) have significantly improved neural speech recognition and understanding. While existing research has examined how well SLMs encode s…
DMOSpeech 2: Reinforcement Learning for Duration Prediction in Metric-Optimized Speech Synthesis
Yinghao Aaron Li, Xilin Jiang, Fei Tao +4
Diffusion-based text-to-speech (TTS) systems have made remarkable progress in zero-shot speech synthesis, yet optimizing all components for perceptual metrics remains challenging.…
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang +2
Blind Speech Separation (BSS) aims to separate multiple speech sources from audio mixtures recorded by a microphone array. The problem is challenging because it is a blind inverse…
Bridging Ears and Eyes: Analyzing Audio and Visual Large Language Models to Humans in Visible Sound Recognition and Reducing Their Sensory Gap via Cross-Modal Distillation
Xilin Jiang, Junkai Wu, Vishal Choudhari +1
Audio large language models (LLMs) are considered experts at recognizing sound objects, yet their performance relative to LLMs in other sensory modalities, such as visual or audio-…
AAD-LLM: Neural Attention-Driven Auditory Scene Understanding
Xilin Jiang, Sukru Samet Dindar, Vishal Choudhari +6
Auditory foundation models, including auditory large language models (LLMs), process all sound inputs equally, independent of listener perception. However, human auditory perceptio…
Exploring Finetuned Audio-LLM on Heart Murmur Features
Adrian Florea, Xilin Jiang, Nima Mesgarani +1
Large language models (LLMs) for audio have excelled in recognizing and analyzing human speech, music, and environmental sounds. However, their potential for understanding other ty…