Speaker Identification with Whispered Speech for the Access Control System

Jia Ching Wang, Yu Hao Chin, Wen Chi Hsieh, Chang Hong Lin, Ying Ren Chen, Ernestasia Siahaan

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

This work presents an access control system, which is a speaker identification system based on whispered speech. Speaker identification is a main function of an access control system. Hence, a novel speaker identification system using instantaneous frequencies is proposed. The input speech signals pass through both signal independent and signal dependent filters firstly. Then, we derive the signal's instantaneous frequencies by applying the Hilbert transform. The analyzed instantaneous frequencies are proceeded to be modeled as probability density models. We use these probability density models as the feature in the proposed speaker identification system. In this work, we compare the use of parametric and nonparametric probability density estimation for instantaneous frequency modeling. Furthermore, we propose an approximated probability product kernel support vector machine (APPKSVM). In the APPKSVM, Riemann sum is applied in approximating the probability product kernel. The whisper sounds from the CHAIN speech corpus were used in the experiments. Results of the experiments show the superiority of the proposed speaker identification system.

Original languageEnglish
Article number7229351
Pages (from-to)1191-1199
Number of pages9
JournalIEEE Transactions on Automation Science and Engineering
Volume12
Issue number4
DOIs
StatePublished - Oct 2015

Keywords

  • Empirical mode decomposition (EMD)
  • Hilbert-Huang transform
  • instantaneous frequency
  • speaker recognition
  • whispered speech

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