Verification effectiveness in open-set speaker identification

被引:18
|
作者
Ariyaeeinia, A. M. [1 ]
Fortuna, J.
Sivakumaran, P.
Malegaonkar, A.
机构
[1] Univ Hertfordshire, Sch Elect Communo & Elect Engn, Hatfield AL10 9AB, Herts, England
[2] Canon Res Ctr Euorpe Ltd, Bracknell RG12 2XH, Berks, England
来源
关键词
D O I
10.1049/ip-vis:20050273
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Verification effectiveness in open-set, text-independent speaker identification is the authors' primary subject of concern. The study includes an analysis of the characteristics of this mode of speaker recognition and the potential causes of errors. The use of well-known score normalisation techniques for the purpose of enhancing the reliability of the process is described and their relative effectiveness is experimentally investigated. The experiments are based on the dataset proposed for the I-speaker detection task of the NIST Speaker Recognition Evaluation 2003. On the basis of experimental results, it is demonstrated that significant benefits are achieved by using score normalisation in open-set identification, and that the level of this depends highly on the type of approach adopted. The results also show that better performance can be achieved by using the cohort normalisation methods. In particular, the unconstrained cohort method with a relatively small cohort size appears to outperform all other approaches.
引用
收藏
页码:618 / 624
页数:7
相关论文
共 50 条
  • [21] Self-Supervised Open-Set Speaker Recognition with Laguerre-Voronoi Descriptors
    Ohi, Abu Quwsar
    Gavrilova, Marina L.
    SENSORS, 2024, 24 (06)
  • [22] TASK-AGNOSTIC OPEN-SET PROTOTYPE FOR FEW-SHOT OPEN-SET RECOGNITION
    Kim, Byeonggeun
    Lee, Jun-Tae
    Shim, Kyuhong
    Chang, Simyung
    2023 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2023, : 31 - 35
  • [23] A Scalable Open-Set ECG Identification System Based on Compressed CNNs
    Wu, Shun-Chi
    Wei, Shih-Ying
    Chang, Chun-Shun
    Swindlehurst, A. Lee
    Chiu, Jui-Kun
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (08) : 4966 - 4980
  • [24] Multi-Classifier Fusion for Open-Set Specific Emitter Identification
    Zhao, Yurui
    Wang, Xiang
    Lin, Ziyu
    Huang, Zhitao
    REMOTE SENSING, 2022, 14 (09)
  • [25] ORALI: Open-set recognition and active learning for unknown lithology identification
    Zhu, Xinyi
    Zhang, Hongbing
    Ren, Quan
    Rui, Jianwen
    Zhang, Lingyuan
    Zhang, Dailu
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2024, 133
  • [26] Open-set face identification with index-of-max hashing by learning
    Dong, Xingbo
    Kim, Soohyung
    Jin, Zhe
    Hwang, Jung Yeon
    Cho, Sangrae
    Teoh, Andrew Beng Jin
    PATTERN RECOGNITION, 2020, 103
  • [27] A Low-Latency Approach for RFF Identification in Open-Set Scenarios
    Zhang, Bo
    Zhang, Tao
    Ma, Yuanyuan
    Xi, Zesheng
    He, Chuan
    Wang, Yunfan
    Lv, Zhuo
    ELECTRONICS, 2024, 13 (02)
  • [28] Statistical identification guided open-set domain adaptation in fault diagnosis
    Yu, Xiaolei
    Zhao, Zhibin
    Zhang, Xingwu
    Chen, Xuefeng
    Cai, Jianbing
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2023, 232
  • [29] A Research of Gas Open-Set Identification Based on Data Augmentation Algorithm
    Zhu, Ye
    Wang, Jingya
    IEEE ACCESS, 2023, 11 : 18252 - 18260
  • [30] OPEN-SET METRIC LEARNING FOR PERSON RE-IDENTIFICATION IN THE WILD
    Sikdar, Arindam
    Chatterjee, Dibyadip
    Bhowmik, Arpan
    Chowdhury, Ananda S.
    2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2020, : 2356 - 2360