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Liang He

12 papers hereh-index 16785 citations70 works total

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

author position
  • first author3
  • middle author6
  • last author3

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.SD8
  • eess.AS4
same name
  • Liang He — 47 papers, h 14
  • Liang He — 14 papers, h 6
  • Liang He — 12 papers, h 8
  • Liang He — 9 papers, h 4
  • Liang He — 8 papers, h 34
  • Liang He — 7 papers, h 24

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
20172023
most citedLarge Margin Softmax Loss for Speaker Verification

17 citations · 18 across the 7 of their papers we have counts for

collaborators
Showing eess.ASShow all

4 papers · 1 filter

eess.AS2023

Graph Neural Network Backend for Speaker Recognition

Liang He, Ruida Li, Mengqi Niu

Currently, most speaker recognition backends, such as cosine, linear discriminant analysis (LDA), or probabilistic linear discriminant analysis (PLDA), make decisions by calculatin…

eess.AS2022

I4U System Description for NIST SRE'20 CTS Challenge

Kong Aik Lee, Tomi Kinnunen, Daniele Colibro +23

This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge. The I4U's submission was resu…

eess.AS2019

Adaptive Multi-scale Detection of Acoustic Events

Wenhao Ding, Liang He

The goal of acoustic (or sound) events detection (AED or SED) is to predict the temporal position of target events in given audio segments. This task plays a significant role in sa…

eess.AS2019

Latent Class Model with Application to Speaker Diarization

Liang He, Xianhong Chen, Can Xu +3

In this paper, we apply a latent class model (LCM) to the task of speaker diarization. LCM is similar to Patrick Kenny's variational Bayes (VB) method in that it uses soft informat…

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