As people age, structural as well as neural degeneration occurs throughout the auditory system. Many older adults experience difficulty in understanding speech especially in adverse listening conditions although they can hear speech sounds. According to a report of the Committee on Hearing and Bioacoustics and Biomechanics of the National Research Council, peripheral, central-auditory, and cognitive systems have long been considered major factors affecting the understanding of speech. The present study aims to review 1) age-related changes in the peripheral, central-auditory, and cognitive systems, 2) the resulting decline in the understanding of speech, and 3) the clinical implication for audiologic rehabilitation of older adults. Once the factors affecting the understanding of speech in older adults are identified and the characteristics of age-related speech understanding difficulties are examined, clinical management could be developed for prevention and treatment. Future research about problems related to the understanding of speech in older adults will help to improve the quality of life in the elderly.

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. 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. 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. 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.