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Speech Intelligibility for Target and Masker with Different Spectra.
Thibaud Leclère1, David Théry2, Mathieu Lavandier2
1Laboratoire Génie Civil et Bâtiment, ENTPE, Université de Lyon, Rue Maurice Audin, 69518, Vaulx-en-Velin, France. thibaud.leclere@entpe.fr.
Advances in Experimental Medicine and Biology
|April 16, 2016
Summary
The Speech Intelligibility Index (SII) may not accurately reflect speech understanding with filtered sounds. Speech reception thresholds varied more than expected with signal-to-noise ratios beyond the assumed effective range.
Area of Science:
- Acoustics
- Psychoacoustics
- Speech Perception
Background:
- The Speech Intelligibility Index (SII) assumes signal-to-noise ratios (SNRs) outside [-15 dB; +15 dB] do not affect speech intelligibility.
- This assumption is crucial for predicting speech understanding in various acoustic environments.
Purpose of the Study:
- To experimentally evaluate the validity of the SII's assumed effective SNR range for speech intelligibility.
- To investigate how speech reception thresholds (SRTs) are affected by SNRs beyond the conventional [-15 dB; +15 dB] range using filtered signals.
Main Methods:
- Four experiments measured SRTs using speech and speech-spectrum noise.
- Target or noise signals were filtered (high-pass or low-pass) above/below 1400 Hz with varying attenuation levels.
- This manipulation created different SNRs in specific frequency bands to test SII assumptions.
Main Results:
- SRTs initially varied linearly with attenuation but reached an asymptote at high levels.
- The -15 dB SII limit held for high-pass filtered targets but not low-pass filtered targets.
- Speech intelligibility continued to improve with increasing SNR beyond +15 dB for filtered noise, up to +43 dB.
- Filtering noise had a greater impact on SRT reduction than filtering the target signal.
Conclusions:
- The study's findings challenge the SII's assumed SNR range and importance function, particularly for sharply filtered speech signals.
- The results suggest that the SII may overestimate or underestimate speech intelligibility in conditions with spectrally limited signals.
- Further research is needed to refine the SII model for more accurate predictions in complex auditory scenarios.
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