Bartelds Martijn, Richter Caitlin, Liberman Mark, Wieling Martijn
Center for Language and Cognition, Faculty of Arts, University of Groningen, Groningen, Netherlands.
Department of Linguistics, University of Pennsylvania, Philadelphia, PA, United States.
Front Artif Intell. 2020 May 29;3:39. doi: 10.3389/frai.2020.00039. eCollection 2020.
We present an acoustic distance measure for comparing pronunciations, and apply the measure to assess foreign accent strength in American-English by comparing speech of non-native American-English speakers to a collection of native American-English speakers. An acoustic-only measure is valuable as it does not require the time-consuming and error-prone process of phonetically transcribing speech samples which is necessary for current edit distance-based approaches. We minimize speaker variability in the data set by employing speaker-based cepstral mean and variance normalization, and compute word-based acoustic distances using the dynamic time warping algorithm. Our results indicate a strong correlation of = -0.71 ( < 0.0001) between the acoustic distances and human judgments of native-likeness provided by more than 1,100 native American-English raters. Therefore, the convenient acoustic measure performs only slightly lower than the state-of-the-art transcription-based performance of = -0.77. We also report the results of several small experiments which show that the acoustic measure is not only sensitive to segmental differences, but also to intonational differences and durational differences. However, it is not immune to unwanted differences caused by using a different recording device.
我们提出了一种用于比较发音的声学距离度量方法，并通过将非美国英语母语者的语音与美国英语母语者的语音集合进行比较，应用该度量方法来评估美国英语中的外国口音强度。仅基于声学的度量方法很有价值，因为它不需要当前基于编辑距离的方法所必需的对语音样本进行耗时且容易出错的语音转录过程。我们通过采用基于说话者的倒谱均值和方差归一化来最小化数据集中的说话者变异性，并使用动态时间规整算法计算基于单词的声学距离。我们的结果表明，声学距离与1100多名美国英语母语评分者对母语相似度的人类判断之间存在很强的相关性，相关系数为 = -0.71（ < 0.0001）。因此，这种便捷的声学度量方法的表现仅略低于基于转录的最先进方法的表现 = -0.77。我们还报告了几个小型实验的结果，这些结果表明，声学度量方法不仅对音段差异敏感，而且对语调差异和时长差异也敏感。然而，它无法避免因使用不同录音设备而产生的不必要差异。
