Log-linear modeling of consonant confusion data.
Log-linear modeling of consonant confusion data.
复制标题
辅音混淆数据的对数线性建模。
DOI：
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发表时间：
1986
影响因子：
2.4
通讯作者：
J. Dubno
中科院分区：
文献类型：
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作者：
T. Bell;D. Dirks;H. Levitt;J. Dubno
对数线性模型，结合G2统计，开发和应用到现有的几套辅音混淆数据。辅音错误模式与信噪比（S/N），呈现水平，元音上下文，低通和高通滤波的显着相互作用。这些变量也表现出显着的相互作用与错误模式时，分类的基础上的功能分类。错误的模式显着改变了S/N的发音（前，中，后），发声，摩擦，鼻音的地方。低通滤波显着影响错误模式时，按发音，持续时间，或鼻音的地方分类，而高通滤波只影响发声和摩擦错误模式。本文还演示了对数线性建模技术在混淆矩阵分析应用中的实用性：可以测试特定的效果;矩阵中的变异细胞可以相对于特定的感兴趣模型进行隔离;对角细胞可以从分析中消除;矩阵可以跨变量水平折叠，不违反独立性。最后，对数线性技术的发展，提出了简约和预测模型的语音感知。
Log-linear models, in conjunction with the G2 statistic, were developed and applied to several existing sets of consonant confusion data. Significant interactions of consonant error patterns were found with signal-to-noise ratio (S/N), presentation level, vowel context, and low-pass and high-pass filtering. These variables also showed significant interactions with error patterns when categorized on the basis of feature classifications. Patterns of errors were significantly altered by S/N for place of articulation (front, middle, back), voicing, frication, and nasality. Low-pass filtering significantly affected error patterns when categorized by place of articulation, duration, or nasality; whereas, high-pass filtering only affected voicing and frication error patterns. This paper also demonstrates the utility of log-linear modeling techniques in applications to confusion matrix analysis: specific effects can be tested; variant cells in a matrix can be isolated with respect to a particular model of interest; diagonal cells can be eliminated from the analysis; and the matrix can be collapsed across levels of variables, with no violation of independence. Finally, log-linear techniques are suggested for development of parsimonious and predictive models of speech perception.