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. 2015 Apr;19(1):39-44.
doi: 10.7874/jao.2015.19.1.39. Epub 2015 Apr 17.

Speech Recognition in Real-Life Background Noise by Young and Middle-Aged Adults with Normal Hearing

Ji Young Lee  1 , Jin Tae Lee  2 , Hye Jeong Heo  2 , Chul-Hee Choi  1 , Seong Hee Choi  1 , Kyungjae Lee  1
Affiliations

Speech Recognition in Real-Life Background Noise by Young and Middle-Aged Adults with Normal Hearing

Ji Young Lee et al. J Audiol Otol. 2015 Apr.

Erratum in

Abstract

Background and objectives: People usually converse in real-life background noise. They experience more difficulty understanding speech in noise than in a quiet environment. The present study investigated how speech recognition in real-life background noise is affected by the type of noise, signal-to-noise ratio (SNR), and age.

Subjects and methods: Eighteen young adults and fifteen middle-aged adults with normal hearing participated in the present study. Three types of noise [subway noise, vacuum noise, and multi-talker babble (MTB)] were presented via a loudspeaker at three SNRs of 5 dB, 0 dB, and -5 dB. Speech recognition was analyzed using the word recognition score.

Results: 1) Speech recognition in subway noise was the greatest in comparison to vacuum noise and MTB, 2) at the SNR of -5 dB, speech recognition was greater in subway noise than vacuum noise and in vacuum noise than MTB while at the SNRs of 0 and 5 dB, it was greater in subway noise than both vacuum noise and MTB and there was no difference between vacuum noise and MTB, 3) speech recognition decreased as the SNR decreased, and 4) young adults showed better speech recognition performance in all types of noises at all SNRs than middle-aged adults.

Conclusions: Speech recognition in real-life background noise was affected by the type of noise, SNR, and age. The results suggest that the frequency distribution, amplitude fluctuation, informational masking, and cognition may be important underlying factors determining speech recognition performance in noise.

Keywords: Age; Real-life background noise; Signal-to-noise ratio; Speech recognition; Speech recognition in noise.

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Figures

Fig. 1
Fig. 1. Frequency spectra (colored) and peak amplitude (black line) at 20 seconds after onset of the noise stimuli. MTB: multi-talker babble.
Fig. 2
Fig. 2. Waveforms of the noise stimuli.
Fig. 3
Fig. 3. Word recognition score by the noise type at the signal-tonoise ratios of 5 dB, 0 dB, and -5 dB. Error bars indicate 1 standard error from the mean. SNR: signal-to-noise ratio, MTB: multitalker babble.
Fig. 4
Fig. 4. Word recognition score by the noise type and SNR in young and middle-aged adults. Error bars indicate 1 standard error from the mean. SNR: signal-to-noise ratio, MTB: multitalker babble.
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