spoken-arabic-digit

OpenML dataset with id 1503

Author name not available (Why is that?)

Full work available at URL: https://api.openml.org/data/v1/download/1592295/spoken-arabic-digit.arff

Upload date: 25 May 2015

Dataset Characteristics

Number of classes: 10
Number of features: 15 (numeric: 14, symbolic: 1 and in total binary: 0 )
Number of instances: 263,256
Number of instances with missing values: 0
Number of missing values: 0

Description

Author: Data Collected by the Laboratory of Automatic and Signals, University of Badji-Mokhtar Annaba, Algeria. Source: UCI Please cite:

Title of Database: Spoken Arabic Digit

Abstract:

This dataset contains time series of mel-frequency cepstrum coefficients (MFCCs) corresponding to spoken Arabic digits. Includes data from 44 males and 44 females native Arabic speakers.

Source:

Data Collected by the Laboratory of Automatic and Signals, University of Badji-Mokhtar Annaba, Algeria.

Direction: Prof.Mouldi Bedda Participants: H.Dahmani, C.Snani, MC.Amara Korba, S.Atoui Adapted and preprocessed by : Nacereddine Hammami and Mouldi Bedda Faculty of Engineering, Al-Jouf University Sakaka, Al-Jouf Kingdom of Saudi Arabia e-mail: nacereddine.hammami '@' gmail.com mouldi_bedda '@' yahoo.fr Date: October, 2008

Data Set Information:

Dataset from 8800 (10 digits x 10 repetitions x 88 speakers) time series of 13 Frequency Cepstral Coefficients (MFCCs) had taken from 44 males and 44 females Arabic native speakers between the ages 18 and 40 to represent ten spoken Arabic digit.

Attribute Information:

Each line on the data base represents 13 MFCCs coefficients in the increasing order separated by spaces. This corresponds to one analysis frame. The 13 Mel Frequency Cepstral Coefficients (MFCCs) are computed with the following conditions; Sampling rate: 11025 Hz, 16 bits Window applied: hamming Filter pre-emphasized: 1-0.97Z^(-1)

Relevant Papers:

[1] N. Hammami, M. Bedda ,"Improved Tree model for Arabic Speech Recognition", Proc. IEEE ICCSIT10 Conference, 2010. [2] N. Hammami, M. Sellami ,"Tree distribution classifier for automatic spoken Arabic digit recognition", Proc. IEEE ICITST09 Conference, 2009 , PP 1-4.

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