Reintroducing KAPD as a Dataset for Machine Learning and Data Mining Applications

被引：3

作者：

Seddiq, Yasser ^{[1
,2
]}

Meftah, Ali ^{[2
]}

Alghamdi, Mansour ^{[1
]}

Alotaibi, Yousef ^{[2
]}

机构：

[1] King Abdulaziz City Sci & Technol, Riyadh, Saudi Arabia

[2] King Saud Univ, Coll Comp & Informat Sci, Riyadh, Saudi Arabia

来源：

UKSIM-AMSS 10TH EUROPEAN MODELLING SYMPOSIUM ON COMPUTER MODELLING AND SIMULATION (EMS) | 2016年

关键词：

imbalanced dataset; speech processing; KAPD; Arabic; corpus; data mining; machine learning;

D O I：

10.1109/EMS.2016.21

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

KACST Arabic Phonetic Database (KAPD) has been in use by researchers for around fifteen years since its initial release. Researches in acoustics and phonetics have benefited from its phonetically rich content. In fact, KAPD has the potential to go further steps with the research community. In this work, KAPD is subject to enhancements and improvements in order to serve as dataset for machine learning and data mining application. This work involves refining and reviewing the already existing metadata of KAPD and adding new material that are necessary for machine learning and data mining applications. The updated phoneme statistics after the corpus upgrade are presented from different perspectives. Data format and time units are made compatible with those of HTK. The paper discusses the potential of KAPD to serve as either a balanced or an imbalanced dataset.

引用

页码：70 / 74

页数：5

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