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EmoFilm - A multilingual emotional speech corpus

Authors: Emilia Parada-Cabaleiro; Giovanni Costantini; Anton Batliner; Alice Baird; Bjoern Schuller;

EmoFilm - A multilingual emotional speech corpus

Abstract

EmoFilm is a multilingual emotional speech corpus comprising 1115 audio instances produced in English, Italian, and Spanish languages. The audio clips (with a mean length of 3.5 sec. and std 1.2 sec.) were extracted in wave format (uncompressed, mono, 48 kHz sample rate and 16-bit) from 43 films (original in English and their over-dubbed Italian and Spanish versions). Genres including comedy, drama, horror, and thriller were considered; anger, contempt, happiness, fear, and sadness emotional states were taken into account. EmoFilm has been presented at Interspeech 2018: Emilia Parada-Cabaleiro, Giovanni Costantini, Anton Batliner, Alice Baird, and Björn Schuller (2018), Categorical vs Dimensional Perception of Italian Emotional Speech, in Proc. of Interspeech, Hyderabad, India, pp. 3638-3642 . We would like to thank Linda Ratz for her contribution in the generation of the transcriptions. How to access EmoFilm To get access to the dataset, please send the signed End User License Agreement (EULA) when making the request. The EULA must be signed by somebody from a university holding a permanent position, typically a full professor. Note that requests without an EULA appropriately filled out, as well as those performed from a non-institutional e-mail address, will be automatically rejected. Please download the EULA from the following link: https://drive.google.com/file/d/1pFHfsqk7snF_EVqq0WAC0Dz8FcTD3s9_/view?usp=share_link

In version 3, a typo in the readme file concerning the emotional labels was fixed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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