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Speaker identification from the sound of the human breath

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arxiv 1712.00171 v2 pith:XEH67UAL submitted 2017-12-01 cs.SD eess.ASstat.ML

classification cs.SDeess.ASstat.ML
keywords soundsinhalationspeakerbreathspeechcharacteristiccontinuousduring
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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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  1. FeatureSense: Protecting Speaker Attributes in Always-On Audio Sensing System

    cs.SD 2025-05 conditional novelty 6.0 of 10

    FeatureSense exposes hand-picked audio features instead of raw audio and introduces the SILI metric, claiming 60.6% lower speaker attribute leakage while keeping sound classification accuracy.

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