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Run Yang

9 papers hereh-index 6167 citations15 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author7

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.SD8
  • cs.LG1
same name
  • Run Yang — 19 papers, h 10
  • Run Yang — 7 papers, h 4
  • Run Yang — 3 papers, h 1
  • Run Yang — 2 papers, h 3
  • Run Yang — 1 paper, h 5
  • Run Yang — 1 paper, h 0

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222025
most citedAn efficient encoder-decoder architecture with top-down attention for speech separation

16 citations · 28 across the 9 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.SD2025

GLM-TTS Technical Report

Jiayan Cui, Zhihan Yang, Naihan Li +10

This work proposes GLM-TTS, a production-level TTS system designed for efficiency, controllability, and high-fidelity speech generation. GLM-TTS follows a two-stage architecture, c…

cs.SD2025

Enhancing Spectrogram Realism in Singing Voice Synthesis via Explicit Bandwidth Extension Prior to Vocoder

Runxuan Yang, Kai Li, Guo Chen +1

This paper addresses the challenge of enhancing the realism of vocoder-generated singing voice audio by mitigating the distinguishable disparities between synthetic and real-life r…

cs.SD2025

A Fast and Lightweight Model for Causal Audio-Visual Speech Separation

Wendi Sang, Kai Li, Runxuan Yang +2

Audio-visual speech separation (AVSS) aims to extract a target speech signal from a mixed signal by leveraging both auditory and visual (lip movement) cues. However, most existing…

cs.SD2025

Time-Frequency-Based Attention Cache Memory Model for Real-Time Speech Separation

Guo Chen, Kai Li, Runxuan Yang +1

Existing causal speech separation models often underperform compared to non-causal models due to difficulties in retaining historical information. To address this, we propose the T…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.