Publications by authors named "Gregory A Ruark"
Utterance clustering is one of the actively researched topics in audio signal processing and machine learning. This study aims to improve the performance of utterance clustering by processing multichannel (stereo) audio signals. Processed audio signals were generated by combining left- and right-channel audio signals in a few different ways and then by extracting the embedded features (also called -vectors) from those processed audio signals.
View Article and Find Full Text PDFIt has long been claimed that certain configurations of facial movements are universally recognized as emotional expressions because they evolved to signal emotional information in situations that posed fitness challenges for our hunting and gathering hominin ancestors. Experiments from the last decade have called this particular evolutionary hypothesis into doubt by studying emotion perception in a wider sample of small-scale societies with discovery-based research methods. We replicate these newer findings in the Hadza of Northern Tanzania; the Hadza are semi-nomadic hunters and gatherers who live in tight-knit social units and collect wild foods for a large portion of their diet, making them a particularly relevant population for testing evolutionary hypotheses about emotion.
View Article and Find Full Text PDFArticle Synopsis
- Many studies on how people from different cultures understand emotions use a task where they pick the correct emotion from a list.
- There's a debate about whether this task makes it easier for people to guess correctly, which might make it seem like everyone understands emotions the same way.
- Research with groups from a small tribe in Tanzania and large cities in China and the U.S. shows that this task can influence how well people do, suggesting that what people pick might not really mean that emotions are universal across cultures.