ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2403.03411
  4. Cited By
CrossNet: Leveraging Global, Cross-Band, Narrow-Band, and Positional
  Encoding for Single- and Multi-Channel Speaker Separation

CrossNet: Leveraging Global, Cross-Band, Narrow-Band, and Positional Encoding for Single- and Multi-Channel Speaker Separation

6 March 2024
Vahid Ahmadi Kalkhorani
DeLiang Wang
ArXivPDFHTML

Papers citing "CrossNet: Leveraging Global, Cross-Band, Narrow-Band, and Positional Encoding for Single- and Multi-Channel Speaker Separation"

3 / 3 papers shown
Title
Exploring Self-Attention Mechanisms for Speech Separation
Exploring Self-Attention Mechanisms for Speech Separation
Cem Subakan
Mirco Ravanelli
Samuele Cornell
François Grondin
Mirko Bronzi
19
23
0
06 Feb 2022
Sandglasset: A Light Multi-Granularity Self-attentive Network For
  Time-Domain Speech Separation
Sandglasset: A Light Multi-Granularity Self-attentive Network For Time-Domain Speech Separation
Max W. Y. Lam
Jun Wang
Dan Su
Dong Yu
AI4TS
67
49
0
01 Mar 2021
Dual-Path Transformer Network: Direct Context-Aware Modeling for
  End-to-End Monaural Speech Separation
Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation
Jing-jing Chen
Qi-rong Mao
Dong Liu
54
279
0
28 Jul 2020
1