In-vehicle speech intelligibility for different driving conditions using the Speech Transmission Index

Samardzic, Nikolina; Novak, Colin

doi:10.3397/1.3598380

Cited by 15 publications

(5 citation statements)

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“…However, the STI is also more measurement intensive, as it involves measurements of amplitude modulation transfer functions 6 or impulse responses 31,32 to characterize reverberation. For listening in vehicles, the effects of reverberation are negligible and speech intelligibility, as quantified by the STI, is primarily limited by the long-term average characteristics of the background noise 23 .…”

Section: Predictions Of Traditional Speech Intelligibility Metrics 21...mentioning

confidence: 99%

“…For the SII, scores > 0.75 are usually taken as indicating good speech communication, while poor communication systems have an SII < 0.45 5 . STI scores for speech in car noise have been interpreted in the following way: > 0.75 -good or excellent speech communication; 0.6 to 0.75 -good communication; 0.45 to 0.6 -fair communication; 0.3 to 0.45 -poor communication; <0.3 -almost no intelligibility 23,24,25 .…”

Section: Predictions Of Traditional Speech Intelligibility Metrics 21...mentioning

confidence: 99%

“…Also, there are no recommendations about how to combine metric values across ears. This may be one factor that contributes to the finding that these metrics do not give accurate predictions of the intelligibility of speech in vehicle noise 23,24,25,35,36,37 .…”

Section: Predictions Of Traditional Speech Intelligibility Metrics 21...mentioning

confidence: 99%

“…The present analysis utilizes the raw data, specifically the speech and noise spectra at the SRT, of Samardzic et al 22 . In the present study, the SII and STI were calculated using the spectrum of the speech material actually used for the SRT measurements, whereas previously 23,24,25 the SII metric was calculated based on the speech spectrum for normal vocal effort, as specified in the ANSI standard for the SII 5 . The calculations of the STI at the SRT (Table 2) have not previously been published.…”

Section: Introductionmentioning

confidence: 99%

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Binaural speech-to-noise loudness ratio at the speech reception threshold in vehicles

Samardzic

Moore

2021

noise cont engng j

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Traditional methods for predicting the intelligibility of speech in the presence of noise inside a vehicle, such as the Articulation Index (AI), the Speech Intelligibility Index (SII), and the Speech Transmission Index (STI), are not accurate, probably because they do not take binaural listening into account; the signals reaching the two ears can differ markedly depending on the positions of the talker and listener. We propose a new method for predicting the intelligibility of speech in a vehicle, based on the ratio of the binaural loudness of the speech to the binaural loudness of the noise, each calculated using the method specified in ISO 532-2 (2017). The method was found to give accurate predictions of the speech reception threshold (SRT) measured under a variety of conditions and for different positions of the talker and listener in a car. The typical error in the predicted SRT was 1.3 dB, which is markedly smaller than estimated using the SII and STI (2.0 dB and 2.1 dB, respectively).

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Section: Predictions Of Traditional Speech Intelligibility Metrics 21...mentioning

confidence: 99%

Section: Predictions Of Traditional Speech Intelligibility Metrics 21...mentioning

confidence: 99%

Section: Predictions Of Traditional Speech Intelligibility Metrics 21...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Binaural speech-to-noise loudness ratio at the speech reception threshold in vehicles

Samardzic

Moore

2021

noise cont engng j

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“…Lee et al 11 revealed that engine and mechanical/electrical noises mainly comprise luxury vehicle noise and analyzed the contribution ratio of each source to the sound quality of interior noise using subjective sound quality correlation and objective parameters. Samardzic and Novak 12 devised a sound quality objective quantification model, which was applied to a commercial vehicle through numerous subjective and objective evaluation tests. Yoon et al 13 studied the sound quality of the heating, ventilation, and air conditioning system of a vehicle using a neural network model and subsequently built a subjectivity and objectivity correlation model.…”

Section: Introductionmentioning

confidence: 99%

Study on the order target of the sporty sound quality of the vehicle exhaust noise under acceleration

Yan

Xiao

Liu

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part D:

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Correlational studies of order noise sample tuning and subjective evaluation test of sound quality were conducted to achieve sporty sound quality and confirm the correlation between the auditory sense (subjective) and the order noise level (objective) of vehicle exhaust noise under acceleration. First, the frequency range and the order ingredient of sporty quality noise were confirmed by a study of ear-hearing subjective feeling on the basis of physiological acoustics. By using an order tuning software that was developed independently, the second, fourth, and sixth order noise A-weighting sound pressure level (dB(A)) of the exhaust noise of an objective vehicle were tuned segmentally into numerous sound samples. Furthermore, samples with high sporty sound quality were selected through subjective evaluation, and the A-weighting sound pressure level (dB(A)) distributions of the second, fourth, and sixth order noise of these samples were analyzed. Consequently, the relative size relations of the second, fourth, and sixth order noise of all the exhaust noise with sporty sound quality were determined. In addition, the curve distribution zones of the corresponding order noise were formed and the order quantitative target of the sporty sound quality was considered. Finally, four passenger vehicles with representative sound qualities (sporty, quiet, and characterless) on the market were selected as the benchmark vehicles; their order noise was objectively tested and their sound qualities subjectively evaluated. Meanwhile, the order noise objective test result was compared with the order target. Results showed that when the fourth and sixth order noise curves relative to the second order noise curves were within the order target zones at most of the engine speeds, the exhaust noise of the vehicle had considerable sporty sound quality; otherwise, it did not have such a sound. Therefore, the order target of the sporty sound quality was accurate and effective.

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Effect of listener head orientation on speech reception threshold in an automotive environment

Liang

Zhou

et al. 2022

Applied Acoustics

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In-vehicle speech intelligibility for different driving conditions using the Speech Transmission Index

Cited by 15 publications

References 0 publications

Binaural speech-to-noise loudness ratio at the speech reception threshold in vehicles

Binaural speech-to-noise loudness ratio at the speech reception threshold in vehicles

Study on the order target of the sporty sound quality of the vehicle exhaust noise under acceleration

Effect of listener head orientation on speech reception threshold in an automotive environment

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