SDASMLDec 1, 2017

Speaker identification from the sound of the human breath

arXiv:1712.00171v212 citations
Originality Highly original
AI Analysis

This addresses speaker identification for security or biometric applications by leveraging a natural and less controlled bio-signature, representing a novel approach in the field.

The paper tackled the problem of speaker identification using breath sounds during inhalation in continuous speech, demonstrating that these sounds alone can achieve remarkably accurate speaker recognition with appropriate feature representations and classification frameworks.

This paper examines the speaker identification potential of breath sounds in continuous speech. Speech is largely produced during exhalation. In order to replenish air in the lungs, speakers must periodically inhale. When inhalation occurs in the midst of continuous speech, it is generally through the mouth. Intra-speech breathing behavior has been the subject of much study, including the patterns, cadence, and variations in energy levels. However, an often ignored characteristic is the {\em sound} produced during the inhalation phase of this cycle. Intra-speech inhalation is rapid and energetic, performed with open mouth and glottis, effectively exposing the entire vocal tract to enable maximum intake of air. This results in vocal tract resonances evoked by turbulence that are characteristic of the speaker's speech-producing apparatus. Consequently, the sounds of inhalation are expected to carry information about the speaker's identity. Moreover, unlike other spoken sounds which are subject to active control, inhalation sounds are generally more natural and less affected by voluntary influences. The goal of this paper is to demonstrate that breath sounds are indeed bio-signatures that can be used to identify speakers. We show that these sounds by themselves can yield remarkably accurate speaker recognition with appropriate feature representations and classification frameworks.

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