The paper proposes an up-to-date literature review of the works using AutoVOT, a discriminative large-margin learning algorithm developed for the semi-automatic measurement of voice onset times. In order to expand the accessibility of the tool in linguistic research, we present VOTEUS, a user-friendly graphic interface written in Python. The interface is conceived to assist the researcher throughout the whole process of annotation, from the forced alignment of the corpora to the refinement of the AutoVOT tier and the extraction of the durations. The general aim is to speed up this phase of data analysis, providing a significant improvement on prevalent practice to date.
Voice Onset Time Enhanced User System (VOTEUS): a web graphic interface for the analysis of plosives’ release phases
Piccardi Duccio;
2018
Abstract
The paper proposes an up-to-date literature review of the works using AutoVOT, a discriminative large-margin learning algorithm developed for the semi-automatic measurement of voice onset times. In order to expand the accessibility of the tool in linguistic research, we present VOTEUS, a user-friendly graphic interface written in Python. The interface is conceived to assist the researcher throughout the whole process of annotation, from the forced alignment of the corpora to the refinement of the AutoVOT tier and the extraction of the durations. The general aim is to speed up this phase of data analysis, providing a significant improvement on prevalent practice to date.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
