Published December 21, 2020 | Version 1.0

A studyforrest extension, an annotation of spoken language in the German dubbed movie ``Forrest Gump'' and its audio-description (validation analysis)

  • 1. Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, 52425, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University, Düsseldorf, 40225, Germany

Description

This component contains the data of the analysis that we ran as a validation of the annotation of speech spoken in the research cut (Hanke et al., 2016) of the movie "Forrest Gump" (Zemeckis, 1994) and its audio-description. The corresponding paper is hosted on github (https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation) and published in f1000research (https://doi.org/10.12688/f1000research.27621.1).

Notes

Here we present an annotation of speech in the audio-visual movie "Forrest Gump" and its audio-description for a visually impaired audience, as an addition to a large public functional brain imaging dataset (studyforrest.org). The annotation provides information about the exact timing of each of the more than 2500 spoken sentences, 16000 words (including 202 non-speech vocalizations), 66000 phonemes, and their corresponding speaker. Additionally, for every word, we provide lemmatization, a simple part-of-speech-tagging (15 grammatical categories), a detailed part-of-speech tagging (43 grammatical categories), syntactic dependencies, and a semantic analysis based on word embedding which represents each word in a 300-dimensional semantic space. To validate the dataset's quality, we build a model of hemodynamic brain activity based on information drawn from the annotation. Results suggest that the annotation's content and quality enable independent researchers to create models of brain activity correlating with a variety of linguistic aspects under conditions of near-real-life complexity

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Additional details

Related works

Is continued by
Dataset: 10.17605/OSF.IO/GFRME (DOI)
Is documented by
Preprint: https://github.com/psychoinformatics-de/studyforrest-paper-speechannotation (URL)
Journal article: 10.12688/f1000research.27621.1 (DOI)
Is supplement to
Dataset: 10.5281/zenodo.4382143 (DOI)