基于自组织映射的语音分集特性研究
Characterisation of speech diversity using self-organising maps
摘要：
我们报告的调查，大量的未标记的语音数据，使用小的手动音素注释语音集的扬声器分类。Kohonen语音打字机是一种半监督的方法，包括自组织映射（SOM），实现低音素出错率。SOM是一个二维单元阵列，它基于邻域学习数据的矢量表示。在本文中，我们报告了一种方法来评估发音使用多层次的SOM与/hVd/单音节发音的元音的研究，澳大利亚的发音。
英文摘要：
We report investigations into speaker classification of larger quantities of unlabelled speech data using small sets of manually phonemically annotated speech. The Kohonen speech typewriter is a semi-supervised method comprised of self-organising maps (SOMs) that achieves low phoneme error rates. A SOM is a 2D array of cells that learn vector representations of the data based on neighbourhoods. In this paper, we report a method to evaluate pronunciation using multilevel SOMs with /hVd/ single syllable utterances for the study of vowels, for Australian pronunciation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
