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Ghadeer-speech-crowd-corpus: Speech dataset.

Ghadeer Qasim Ali¹, Husam Ali Abdulmohsin¹

¹Computer Science Department, College of Science, University of Baghdad, Iraq.

|January 24, 2025

Summary

This summary is machine-generated.

Researchers developed the Ghadeer-Speech-Crowd-Corpus, a new dataset for Arabic and English speech processing. This resource addresses the scarcity of Arabic speech data for applications like speaker identification and speech recognition.

Keywords:

Arabic phrase English phrase Low-resource languages Speech recognition

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Area of Science:

Computational Linguistics
Speech Technology
Data Science

Background:

The scarcity of raw data hinders scientific progress across various fields.
A significant gap exists in publicly available Arabic speech datasets.
Existing datasets often lack diversity in accents and speaker demographics.

Purpose of the Study:

To introduce the Ghadeer-Speech-Crowd-Corpus, a novel Arabic and English speech dataset.
To support advancements in speech processing applications, including speaker identification, text-to-speech, and speech-to-text.
To mitigate the challenge of insufficient data in Arabic speech research.

Main Methods:

Collected speech samples from 210 Iraqi Arab citizens over three months.
Ensured a balanced dataset with respect to sex and language (Arabic/English).
Recorded 15,626 mono audio samples at 44.1 kHz sampling rate, 16-bit depth, and 705.6 kb/s bit rate.

Main Results:

The Ghadeer-Speech-Crowd-Corpus comprises 15,626 balanced Arabic and English speech samples.
The dataset includes diverse accents from various regions of Iraq.
Recordings were conducted at the Academy for Media Training, University of Baghdad.

Conclusions:

The Ghadeer-Speech-Crowd-Corpus provides a valuable resource for the speech technology community.
This dataset will facilitate research and development in Arabic speech processing.
The availability of this corpus addresses a critical need for diverse and comprehensive speech data.