Data
spoken-arabic-digit

spoken-arabic-digit

active ARFF Publicly available Visibility: public Uploaded 25-05-2015 by Rafael G. Mantovani
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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.

15 features

Class (target)nominal10 unique values
0 missing
V1numeric119270 unique values
0 missing
V2numeric91022 unique values
0 missing
V3numeric138180 unique values
0 missing
V4numeric123326 unique values
0 missing
V5numeric135970 unique values
0 missing
V6numeric137186 unique values
0 missing
V7numeric151115 unique values
0 missing
V8numeric146786 unique values
0 missing
V9numeric156467 unique values
0 missing
V10numeric142862 unique values
0 missing
V11numeric150634 unique values
0 missing
V12numeric155756 unique values
0 missing
V13numeric155350 unique values
0 missing
V14numeric2 unique values
0 missing

62 properties

263256
Number of instances (rows) of the dataset.
15
Number of attributes (columns) of the dataset.
10
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
14
Number of numeric attributes.
1
Number of nominal attributes.
-0.14
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
10
The minimal number of distinct values among attributes of the nominal type.
93.33
Percentage of numeric attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
10
The maximum number of distinct values among attributes of the nominal type.
-0.75
Minimum skewness among attributes of the numeric type.
6.67
Percentage of nominal attributes.
-0.01
Third quartile of skewness among attributes of the numeric type.
0.21
Maximum skewness among attributes of the numeric type.
0.5
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
1.41
Third quartile of standard deviation of attributes of the numeric type.
2.75
Maximum standard deviation of attributes of the numeric type.
9.92
Percentage of instances belonging to the least frequent class.
-0.34
First quartile of kurtosis among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
26124
Number of instances belonging to the least frequent class.
-0.64
First quartile of means among attributes of the numeric type.
-0.07
Mean kurtosis among attributes of the numeric type.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
-0.3
Mean of means among attributes of the numeric type.
-0.35
First quartile of skewness among attributes of the numeric type.
0.97
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
0.62
First quartile of standard deviation of attributes of the numeric type.
3.32
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
10
Average number of distinct values among the attributes of the nominal type.
-0.05
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-0.15
Mean skewness among attributes of the numeric type.
-0.32
Second quartile (Median) of means among attributes of the numeric type.
10.06
Percentage of instances belonging to the most frequent class.
1.07
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
26496
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-0.07
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
-2
Minimum kurtosis among attributes of the numeric type.
0
Percentage of binary attributes.
0.78
Second quartile (Median) of standard deviation of attributes of the numeric type.
Third quartile of entropy among attributes.
1.65
Maximum kurtosis among attributes of the numeric type.
-3.08
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
0.27
Third quartile of kurtosis among attributes of the numeric type.
1.98
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.

6 tasks

1 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Class
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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