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February 6, 20260 citationsOpen Access

Effect of masker temporal pattern, spectrum, and presentation level on speech identification.

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VNVijaya Kumar NarneSJSaransh JainRVRM Vaibhav

Key Points

  • This research examines how different masker characteristics affect the identification of speech in noise.
  • Used speech-shaped noise, harmonic complex tone, and iterated ripple noise as maskers.
  • Presented speech with background noise at levels of 50 and 80 dB SPL.
  • Measured identification accuracy at varying signal-to-noise ratios from 0 to -15 dB.
  • Speech identification was best with harmonic complex tone and worst with speech-shaped noise.
  • SNR-50 for speech-shaped noise was worse at 80 dB than at 50 dB, indicating poorer frequency selectivity at higher levels.
  • Harmonic complex tone showed better identification at higher levels, with lower SNR-50 values.

Abstract

The effects of background spectral and temporal structure and overall level on the masking of speech were assessed for sentences presented in a speech-shaped noise (SSN), harmonic complex tone (HCT) (repetition period = 4.55 ms), and iterated ripple noise (IRN) (delay = 4.55 ms). The speech + noise was presented at 50 and 80 dB SPL using signal-to-noise ratios (SNRs) from 0 to -15 dB in 5-dB steps. The noises had similar spectral envelopes, but the HCT and IRN had spectral dips between peaks corresponding to the harmonic frequencies, and the HCT also had temporal dips. Especially for the SNRs of -5 and -10 dB, speech identification was best for the HCT masker and worst for the SSN, for both overall levels. For the SSN, the SNR required for 50% correct (SNR-50) was higher (worse) at 80 dB than at 50 dB, consistent with poorer frequency selectivity at the higher level. For the HCT, SNR-50 values were lower for the higher level, consistent with a better ability to "listen in the dips" at the higher level. The results indicate that the relative benefit of spectral and temporal dips varies with level.

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Cite This Study

Narne et al. (2025) studied this question.

synapsesocial.com/papers/698585aa8f7c464f2300937ahttps://doi.org/10.17863/cam.125378
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Also Consider

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