Phonetics, Phonology, and Morphology

Understanding how deep convolutional neural networks classify data has been subject to extensive research. This paper proposes a technique to visualize and interpret intermediate layers of unsupervised deep convolutional networks by averaging over individual feature maps in each convolutional layer and inferring underlying distributions of words with non-linear regression techniques. A GAN-based architecture (ciwGAN [1]) that includes a Generator, a Discriminator, and a classifier was trained on unlabeled sliced lexical items from TIMIT. The training process results in a deep...

Corpus studies of regional variation using raw language data from the internet focus predominantly on lexical variables in writing. However, online repositories such as YouTube offer the possibility of investigating regional differences using phonological variables, as well. This article demonstrates the viability of constructing a naturalistic speech corpus for sociophonetic research by analyzing hundreds of recitations of Abraham Lincoln's Gettysburg Address. We first replicate a known result of phonetic research, namely, that English vowels are longer in duration before voiced...