沃洛夫语元音长度对比的机器辅助分析
Machine Assisted Analysis of Vowel Length Contrasts in Wolof
摘要：
不断增长的数字档案和改进的文本和语音自动分析算法为语音学的基础研究创造了新的研究机会。这样的经验方法允许统计评估的一个更大的一套假设语音变异及其制约因素（其中包括地理/方言变体）。本文阐述了这一愿景，并提出了挑战自动方法分析一个不容易观察到的现象：元音长度的对比。我们专注于沃洛夫语，这是一种来自撒哈拉以南非洲的资源不足的语言。特别是，我们提出了多个功能，使不同的因素下，如：阅读与半自发的讲话，标准与方言沃洛夫语的长度对比度的程度作出一个很好的评价。我们的措施，完全自动超过20 k元音令牌表明，我们提出的功能可以突出不同程度的对比度为每个元音考虑。我们发现，在半自发言语和不规范的半自发方言中，对比度较弱。
英文摘要：
Growing digital archives and improving algorithms for automatic analysis of text and speech create new research opportunities for fundamental research in phonetics. Such empirical approaches allow statistical evaluation of a much larger set of hypothesis about phonetic variation and its conditioning factors (among them geographical / dialectal variants). This paper illustrates this vision and proposes to challenge automatic methods for the analysis of a not easily observable phenomenon: vowel length contrast. We focus on Wolof, an under-resourced language from Sub-Saharan Africa. In particular, we propose multiple features to make a fine evaluation of the degree of length contrast under different factors such as: read vs semi spontaneous speech ; standard vs dialectal Wolof. Our measures made fully automatically on more than 20k vowel tokens show that our proposed features can highlight different degrees of contrast for each vowel considered. We notably show that contrast is weaker in semi-spontaneous speech and in a non standard semi-spontaneous dialect.
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