EMVD dataset: a dataset of extreme vocal distortion techniques used in heavy metal
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What problem does the paper attempt to solve? Is this a new problem?
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What scientific hypothesis does this paper seek to validate?
This paper aims to validate the scientific hypothesis related to extreme vocal distortion techniques used in heavy metal music. It explores various aspects such as automatic detection of screams and shouted speech in subway trains , acoustic features and auditory impressions of death growl and screaming voice , voice production in death metal singers , and scream detection in heavy metal music . The research delves into the aerodynamic characteristics of growl voice and reinforced falsetto in metal singing , as well as the musical aspects of vowel formants in the extreme metal voice .
What new ideas, methods, or models does the paper propose? What are the characteristics and advantages compared to previous methods?
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Do any related researches exist? Who are the noteworthy researchers on this topic in this field?What is the key to the solution mentioned in the paper?
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How were the experiments in the paper designed?
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What is the dataset used for quantitative evaluation? Is the code open source?
The dataset used for quantitative evaluation of extreme vocal distortion techniques in heavy metal is the Extreme Metal Vocals Dataset (EMVD) . This dataset is comprehensive and diverse, featuring a new taxonomy that includes four distinct distortion techniques across three vocal ranges and three vocal effects . The EMVD dataset is available as open-source, and it can be accessed at the following link: https://zenodo.org/record/8406322, in line with the open science policy of the European Union .
Do the experiments and results in the paper provide good support for the scientific hypotheses that need to be verified? Please analyze.
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