Abstract

ObjectivesThe present study explored tone perception ability in school age Mandarin-speaking children with otitis media with effusion (OME) in noisy listening environments. The study investigated the interaction effects of noise, tone type, age, and hearing status on monaural tone perception, and assessed the application of a hierarchical clustering algorithm for profiling hearing impairment in children with OME.MethodsForty-one children with normal hearing and normal middle ear status and 84 children with OME with or without hearing loss participated in this study. The children with OME were further divided into two subgroups based on their severity and pattern of hearing loss using a hierarchical clustering algorithm. Monaural tone recognition was measured using a picture-identification test format incorporating six sets of monosyllabic words conveying four lexical tones under speech spectrum noise, with the signal-to-noise ratio (SNR) conditions ranging from -9 to -21 dB.ResultsLinear correlation indicated tone recognition thresholds of children with OME were significantly correlated with age and pure tone hearing thresholds at every frequency tested. Children with hearing thresholds less affected by OME performed similarly to their peers with normal hearing. Tone recognition thresholds of children with auditory status more affected by OME were significantly inferior to those of children with normal hearing or with minor hearing loss. Younger children demonstrated poorer tone recognition performance than older children with OME. A mixed design repeated-measure ANCOVA showed significant main effects of listening condition, hearing status, and tone type on tone recognition. Contrast comparisons revealed that tone recognition scores were significantly better under -12 dB SNR than under -15 dB SNR conditions and tone recognition scores were significantly worse under -18 dB SNR than those obtained under -15 dB SNR conditions. Tone 1 was the easiest tone to identify and Tone 3 was the most difficult tone to identify for all participants, when considering -12, -15, and -18 dB SNR as within-subject variables. The interaction effect between hearing status and tone type indicated that children with greater levels of OME-related hearing loss had more impaired tone perception of Tone 1 and Tone 2 compared to their peers with lesser levels of OME-related hearing loss. However, tone perception of Tone 3 and Tone 4 remained similar among all three groups. Tone 2 and Tone 3 were the most perceptually difficult tones for children with or without OME-related hearing loss in all listening conditions.ConclusionsThe hierarchical clustering algorithm demonstrated usefulness in risk stratification for tone perception deficiency in children with OME-related hearing loss. There was marked impairment in tone perception in noise for children with greater levels of OME-related hearing loss. Monaural lexical tone perception in younger children was more vulnerable to noise and OME-related hearing loss than that in older children.

Highlights

  • More than 70% of all the languages in the world are tone languages and approximately one half of the global population speak a tonal language [1]

  • Linear correlation indicated tone recognition thresholds of children with otitis media with effusion (OME) were significantly correlated with age and pure tone hearing thresholds at every frequency tested

  • Tone recognition thresholds of children with auditory status more affected by OME were significantly inferior to those of children with normal hearing or with minor hearing loss

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Summary

Introduction

More than 70% of all the languages in the world are tone languages and approximately one half of the global population speak a tonal language [1]. Tones differ in dimensions of pitch, direction, length, extreme endpoint and slope [2]. Acoustic parameters related with tone primarily include contour and movement of fundamental frequency (F0) [3]. In Mandarin, there are four lexical tones, which can be described as high level (Tone 1), high rising (Tone 2), low dipping (Tone 3) and high falling (Tone 4) based on F0 contours [4]. Tone recognition is primarily cued by F0 and higher harmonics [3, 5, 6]. Amplitude contour, and spectral envelope may be utilized as secondary cues, especially when F0 is compromised [7,8,9,10,11]

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