Tao Duo-Duo, Fu Qian-Jie, Galvin John J, Yu Ya-Feng
Department of Ear, Nose, and Throat, The First Affiliated Hospital of Soochow University, Suzhou 215006, China.
Department of Head and Neck Surgery, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Speech Commun. 2017 Sep;92:125-131. doi: 10.1016/j.specom.2017.06.008. Epub 2017 Jun 30.
Matrix-styled sentence tests offer a closed-set paradigm that may be useful when evaluating speech intelligibility. Ideally, sentence test materials should reflect the distribution of phonemes within the target language. We developed and validated the Closed-set Mandarin Sentence (CMS) test to assess Mandarin speech intelligibility in noise. CMS test materials were selected to be familiar words and to represent the natural distribution of vowels, consonants, and lexical tones found in Mandarin Chinese. Ten key words in each of five categories (Name, Verb, Number, Color, and Fruit) were produced by a native Mandarin talker, resulting in a total of 50 words that could be combined to produce 100,000 unique sentences. Normative data were collected in 10 normal-hearing, adult Mandarin-speaking Chinese listeners using a closed-set test paradigm. Two test runs were conducted for each subject, and 20 sentences per run were randomly generated while ensuring that each word was presented only twice in each run. First, the level of the words in each category were adjusted to produce equal intelligibility in noise. Test-retest reliability for word-in-sentence recognition was excellent according to Cronbach's alpha (0.952). After the category level adjustments, speech reception thresholds (SRTs) for sentences in noise, defined as the signal-to-noise ratio (SNR) that produced 50% correct whole sentence recognition, were adaptively measured by adjusting the SNR according to the correctness of response. The mean SRT was -7.9 (SE=0.41) and -8.1 (SE=0.34) dB for runs 1 and 2, respectively. The mean standard deviation across runs was 0.93 dB, and paired t-tests showed no significant difference between runs 1 and 2 (p=0.74) despite random sentences being generated for each run and each subject. The results suggest that the CMS provides large stimulus set with which to repeatedly and reliably measure Mandarin-speaking listeners' speech understanding in noise using a closed-set paradigm.
矩阵式句子测试提供了一种封闭集范式，在评估言语可懂度时可能会很有用。理想情况下，句子测试材料应反映目标语言中音素的分布情况。我们开发并验证了封闭式汉语句子（CMS）测试，以评估噪声环境下的汉语言语可懂度。CMS测试材料选择了常用词，以代表汉语普通话中元音、辅音和声调的自然分布。由一位说普通话的母语者说出五个类别（姓名、动词、数字、颜色和水果）中每个类别的十个关键词，总共50个词可组合成100,000个独特的句子。使用封闭集测试范式，收集了10名听力正常、说普通话的成年中国听众的标准数据。对每个受试者进行两次测试，每次测试随机生成20个句子，同时确保每个词在每次测试中仅出现两次。首先，调整每个类别的词的水平，使其在噪声中的可懂度相等。根据克朗巴赫α系数，句子中单词识别的重测信度极佳（0.952）。在类别水平调整后，通过根据反应的正确性调整信噪比，自适应地测量噪声中句子的言语接受阈值（SRT），即产生50%正确全句识别的信噪比。第一次和第二次测试的平均SRT分别为-7.9（标准误=0.41）和-8.1（标准误=0.34）dB。两次测试的平均标准差为0.93 dB，配对t检验显示第一次和第二次测试之间无显著差异（p=0.74），尽管每次测试和每个受试者的句子都是随机生成的。结果表明，CMS提供了一个庞大的刺激集，可用于使用封闭集范式反复且可靠地测量说普通话的听众在噪声中的言语理解能力。
