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Related Experiment Video

Updated: Apr 27, 2026

Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
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Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

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Cost-sensitive learning for emotion robust speaker recognition.

Dongdong Li1, Yingchun Yang2, Weihui Dai3

  • 1School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.

Thescientificworldjournal
|July 8, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces cost-sensitive learning to improve speaker recognition accuracy with emotional speech. The new system enhances robustness, achieving an 8% identification rate improvement for emotion-dependent voice biometrics.

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Area of Science:

  • Information Security
  • Biometrics
  • Speech Processing

Background:

  • Voice biometrics are crucial for identity verification.
  • Emotional variations in speech significantly degrade speaker recognition system performance.
  • Existing systems struggle with the high error rates caused by affective speech.

Purpose of the Study:

  • To enhance the robustness of emotion-dependent speaker recognition systems.
  • To address the performance degradation caused by speech emotions.
  • To improve the accuracy of voice biometrics in real-world scenarios.

Main Methods:

  • Introduction of a cost-sensitive learning technology.
  • Reweighting the probability of affective utterances at the pitch envelope level.
  • Proposal of a novel recognition system architecture and its components.

Main Results:

  • Significant enhancement in the robustness of emotion-dependent speaker recognition.
  • An 8% improvement in identification rate compared to traditional speaker recognition methods.
  • Effective handling of speech with various emotions.

Conclusions:

  • Cost-sensitive learning is an effective approach for emotion-dependent speaker recognition.
  • The proposed system architecture improves accuracy and robustness.
  • This technology offers a promising solution for secure and reliable voice biometrics.