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Sudanese dialect speech dataset

Authors: Ayman Mansour;

Sudanese dialect speech dataset

Abstract

This is speech dataset for the Sudanese dialect The data been collected from YouTube videos represent the characteristics of the Sudanese dialect, mainly the middle of Sudan dialect -Khartoum in particular- and have some northern tendency, primarily two programs Hajj Muzakir and Dukkan Wad Elbaseer. Transcription is done manually by listening to the audio files repeatedly to write the captions for the collected conversations to make sure that every word is written as said by the speakers. Transcription is written without diacritics on the Arabic alphabet, in a manner that reflects the Sudanese way of speaking, therefore, any correction to the noticeable mistakes was not applied to get rid of any biases and make the data representative. The 'Dataset' subdirectory contains all the audio and text files for the corpus, the files organized based on program name 'hm_' for Hajj Muzakir program and 'wb_' Dukkan Wad Elbaseer, each filename follows three categories first two litters for the program name 'hm' or 'wb', second the number of the episode third the number of the clip, hm_01_0001.wav and wb_01_0001.wav represent first episode of each program and the first clip.

Keywords

Arabic Language, Dialectal Arabic, Sudanese DIalect

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selected citations
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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).
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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.
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