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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Thorsten-Voice Dataset 2023.09 Hessisch

Authors: Müller, Thorsten; Kreutz, Dominik;

Thorsten-Voice Dataset 2023.09 Hessisch

Abstract

The goal of project "Thorsten-Voice" is to provide voice datasets and TTS models for free and high quality german artificial voice. This dataset "Thorsten-Voice dataset 2023.09 Hessisch" is based on normal german textual input but pronounced in a german regional dialect called "Hessisch". This special dialect is spoken mostly in the southern region of the german state "Hessen". It is recorded by Thorsten Müller, audio optimized by Dominik Kreutz and licenced under CC0 to provide it for anybody without any financial or licence struggle. "I contribute my personal voice as a person believing in a world where all people are equal. No matter of gender, sexual orientation, religion, skin color and geocoordinates of birth location. A global world where everybody is warmly welcome on any place on this planet and open and free knowledge and education is available to everyone." (Thorsten Müller) Dataset details: ljspeech file and directory structure 2.108 recorded phrases (wav files) samplerate 22.050Hz mono normalized to -24dB no silence at beginning/ending See more details on my Github page or Thorsten-Voice project website.

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citations
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!
0
Average
Average
Average