Gender Classification (Male / Female) Through Voice

Elsir Mohamed Osman Alkbashi1 Mohammed Hussien Eltaieb Adam2

Neelain University, Sudan.

Email: neneot449@gmail.com

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HNSJ, 2022, 3(12); https://doi.org/10.53796/hnsj31218

Published at 01/12/2022 Accepted at 10/11/2022

Abstract

Proceeding from the importance of sound in practical life and that it is involved in many fields, we set out with the idea of ​​this project, which makes the computer a tool used to classify human voices and identify the identity of the speaker, whether he is male or female, and since the voice is the summary and the string of sentences, it was necessary to research In the nature of sound and its physical properties, we focused our attention on one of the properties of sound, which is frequency, as the system measures the frequency of the sound signal. The research relied on randomly collected sounds, and then processing this data using the automatic correlation technique to classify gender, male or female, in the right ways, using one of the sound characteristics, which is frequency. The results that have been reached are the success of the classification process for both sexes according to sound quality. Noise, noise and microphone quality directly affect the results of the system in classification, which leads to inaccurate results. Also, the more noise-free the recorded audio signal, the more accurate the results. The efficiency of the autocorrelation technique in calculating the value of the signal frequency.

عنوان البحث

تصنيف النوع (ذكر – انثي) من خلال الصوت

السر محمد عثمان الكباشي1 محمد حسين الطيب آدم2

1 جامعة النيلين، السودان

بريد الكتروني: neneot449@gmail.com

HNSJ, 2022, 3(12); https://doi.org/10.53796/hnsj31218

تاريخ النشر: 01/12/2022م تاريخ القبول: 10/11/2022م

المستخلص

انطلاقا من أهمية الصوت في الحياة العملية وانخراطه في العديد من المجالات ، انطلقنا بفكرة هذا المشروع الذي يجعل الكمبيوتر أداة تستخدم لتصنيف الأصوات البشرية والتعرف على هوية المتحدث سواء كان هو ذكر أو أنثى ، وبما أن الصوت هو الخلاصة وسلسلة الجمل ، كان من الضروري البحث في طبيعة الصوت وخصائصه الفيزيائية ، ركزنا انتباهنا على إحدى خصائص الصوت وهي التردد ، يقيس النظام تردد الإشارة الصوتية. اعتمد البحث على الأصوات التي تم جمعها عشوائياً ، ومن ثم معالجة هذه البيانات باستخدام تقنية الارتباط الآلي لتصنيف الجنس ، ذكراً كان أم أنثى ، بالطرق الصحيحة ، باستخدام إحدى خصائص الصوت وهي التردد. والنتائج التي تم التوصل إليها هي نجاح عملية التصنيف لكلا الجنسين حسب جودة الصوت. التشويش والضوضاء وجودة الميكروفون تؤثر بشكل مباشر على نتائج النظام في التصنيف مما يؤدي إلى نتائج غير دقيقة. كذلك كلما كانت الاشارةة الصوتية المسجلة خالية من الضوضاء كانت النتائج أكثر دقة ، كفاءة تقنية الارتباط الذاتي في حساب قيمة تردد الإشارة.

1. Introduction:

The human voice is the most compatible medium for human interaction. When sound comes out of the vocal tract, it carries a lot of regional, dynamic, and logical atmospheric data. Using these types of information, we can learn about human language, gender, age, dialect, emotional and current state. (40).

Gender recognition is a technique for identifying gender categories by analyzing a speaker’s vocal cues (41)(42).

(43)(44). Moreover, we can see how effective a gender classification system is in many advanced fields such as medical fields in identifying COVID-19 disease – through voice and commercial fields, forensic investigation, robotics, security system, and more.

2. Related Studies

In paper(45) Comparison is drawn between male and female larynges on the basis of overall size, vocal fold membranous length, elastic properties of tissue, and prephonatory glottal shape,in paper(46) An investigation has been reported to determine the importance of sound frequencies, pitch, and source spectrum slope on sound classification. Eight professional singers sang five common vowels on four common tones, and in a forced-choice test, vocal teachers rated the pronunciation as tone, baritone, or bass. Measurements of spoken vowel sounds reveal higher pitched frequencies in the tenor type and lower frequencies in the bass type, This paper (47) presents a pitch-range (PR) based feature set for age and gender classification. The performance of the proposed feature set is compared with MFCCs, energy, relative spectral transform–perceptual linear prediction (RASTA_PLP), and fundamental frequency (F0). Voice activity detection (VAD) is performed to extract speech utterances before feature extraction. Two different classifiers, k-Nearest Neighbors (kNN) and Support Vector Machines (SVM) are used in order to evaluate the effectiveness of the feature sets, in paper(48) It includes developing a gender model for gender recognition from a speech signal. In our current system fuzzy logic is used and

The neural network approach did not produce the exact required result for gender classification due to the complexity of the training network.

To overcome this problem, various evolutionary algorithms such as Genetic Algorithm (GA) are applied in sex classification.in paper(49) Gender classification of audio data. The agenda is to determine gender, using five different algorithms: Discriminant Linear Analysis (LDA), K-type Nearest Neighborhood (KNN), Classification and Regression Trees (CART), Random Forest (RF), and Supporting Vector Machine (SVM) based on eight different scales.in paper(50) A gender classifier was developed using two different data sets in different languages, English and Bahasa Indonesian. Each of the two data sets is represented by 20 audio features. Multi Layer Perceptron (MLP) is used to build the classification model using all these features and is trained only on the English dataset.

3.PROPOSED SYSTEM AND METHODS

The paper proposed a new method, which is to identify the gender (male/female) through the voice using the autocorrelation technique, and the focus was on one of the sound characteristics, which is frequency.A. How the Proposed Solution work

A rating system consists of multiple stages, focusing on one of the characteristics of sound, which is frequency, to know the final result. Through which the entrance sound is classified by both sexes (whether male or female)The proposed system operates in the following stages:

  • Inputs stage.
  • sampling stage
  • Pre-processing stage
  • Classification stage

B. Functional Flow Diagram

The processing of model flow blew diagram figure 3.1.

Input

Sampling

Preprocessing

Classification

Gender

Figure 1: Shows the data flow diagram

The proposed system works in the following states:

  1. Inputs:

At this stage, the system takes the audio signal to be categorized by either real-time recording or by bringing a saved load sound file. There are two ways of the input process, which are as follows:

  • Real-time Record method.
  • the method of fetching or fetching a saved audio file.
  1. Samples:

the input signal is an analog signal, it is converted the analog signal into a digital signal.

  1. Preprocessing:

The sound is filtered from noise or distortion so that the frequency is calculated more accurately

  1. Classification:

This stage is considered one of the most important. At this stage, the basic frequency of the audio signal is calculated, from which a classification process is performed whether the input signal is male or female.

3.Implementation and evolution of system

We have implemented these techniques in Matlab and Auto-Correlation software. Thus, it is important to determine the most appropriate approach to its application. As defined before, there are several stages to the performance of the type classification system

We randomly selected 30 samples, 15 male samples and 15 female samples, 13 samples that were correctly classified as males, and 14 samples that were correctly classified on the basis that they were female, as the system misclassified 3 sample from A out of 15 samples from the adult category that the system aims to classify according to their voices and frequencies.

Table 1: Sample diagnosed results and status.

الحالة نتيجة التصنيف تردد العينة التردد الطبيعي للإناث التردد الطبيعي للذكور الجنس الرقم
True Male 138 186 – 250 Hz 75 – 185 Hz Male 1
True Male 167 186 – 250 Hz 75 – 185 Hz Male 2
True Male 138 186 – 250 Hz 75 – 185 Hz Male 3
True Male 105 186 – 250 Hz 75 – 185 Hz Male 4
True Male 154 186 – 250 Hz 75 – 185 Hz Male 5
True Male 174 186 – 250 Hz 75 – 185 Hz Male 6
True Male 129 186 – 250 Hz 75 – 185 Hz Male 7
True Male 163 186 – 250 Hz 75 – 185 Hz Male 8
True Male 127 186 – 250 Hz 75 – 185 Hz Male 9
True Male 110 186 – 250 Hz 75 – 185 Hz Male 10
False Female 250 186 – 250 Hz 75 – 185 Hz Male 11
True Male 157 186 – 250 Hz 75 – 185 Hz Male 12
True Male 145 186 – 250 Hz 75 – 185 Hz Male 13
False Female 200 186 – 250 Hz 75 – 185 Hz Male 14
True Male 167 186 – 250 Hz 75 – 185 Hz Male 15
True Male 145 186 – 250 Hz 75 – 185 Hz Male 16
True Male 122 186 – 250 Hz 75 – 185 Hz Male 17
True Male 162 186 – 250 Hz 75 – 185 Hz Male 18
True Male 100 186 – 250 Hz 75 – 185 Hz Male 19
True Male 114 186 – 250 Hz 75 – 185 Hz Male 20
True Male 80 186 – 250 Hz 75 – 185 Hz Male 21
True Male 98 186 – 250 Hz 75 – 185 Hz Male 22
True Male 130 186 – 250 Hz 75 – 185 Hz Male 23
True Male 149 186 – 250 Hz 75 – 185 Hz Male 24
True Male 132 186 – 250 Hz 75 – 185 Hz Male 25
True Male 163 186 – 250 Hz 75 – 185 Hz Male 26
True Male 164 186 – 250 Hz 75 – 185 Hz Male 27
True Male 121 186 – 250 Hz 75 – 185 Hz Male 28
True Male 115 186 – 250 Hz 75 – 185 Hz Male 29
True Male 109 186 – 250 Hz 75 – 185 Hz Male 30
True Male 103 186 – 250 Hz 75 – 185 Hz Male 31
True Male 77 186 – 250 Hz 75 – 185 Hz Male 32
True Male 81 186 – 250 Hz 75 – 185 Hz Male 33
True Male 94 186 – 250 Hz 75 – 185 Hz Male 34
True Male 100 186 – 250 Hz 75 – 185 Hz Male 35
True Male 164 186 – 250 Hz 75 – 185 Hz Male 36
True Male 126 186 – 250 Hz 75 – 185 Hz Male 37
True Male 117 186 – 250 Hz 75 – 185 Hz Male 38
True Male 141 186 – 250 Hz 75 – 185 Hz Male 39
True Male 96 186 – 250 Hz 75 – 185 Hz Male 40
True Male 85 186 – 250 Hz 75 – 185 Hz Male 41
True Male 74 186 – 250 Hz 75 – 185 Hz Male 42
True Male 79 186 – 250 Hz 75 – 185 Hz Male 43
True Male 110 186 – 250 Hz 75 – 185 Hz Male 44
True Male 113 186 – 250 Hz 75 – 185 Hz Male 45
True Male 161 186 – 250 Hz 75 – 185 Hz Male 46
True Male 100 186 – 250 Hz 75 – 185 Hz Male 47
True Male 85 186 – 250 Hz 75 – 185 Hz Male 48
True Male 75 186 – 250 Hz 75 – 185 Hz Male 49
True Male 78 186 – 250 Hz 75 – 185 Hz Male 50
True Male 119 186 – 250 Hz 75 – 185 Hz Male 51
True Male 123 186 – 250 Hz 75 – 185 Hz Male 52
True Male 155 186 – 250 Hz 75 – 185 Hz Male 53
True Male 163 186 – 250 Hz 75 – 185 Hz Male 54
True Male 147 186 – 250 Hz 75 – 185 Hz Male 55
True Male 100 186 – 250 Hz 75 – 185 Hz Male 56
True Male 99 186 – 250 Hz 75 – 185 Hz Male 57
True Male 106 186 – 250 Hz 75 – 185 Hz Male 58
True Male 119 186 – 250 Hz 75 – 185 Hz Male 59
True Male 123 186 – 250 Hz 75 – 185 Hz Male 60
True Male 147 186 – 250 Hz 75 – 185 Hz Male 61
True Male 163 186 – 250 Hz 75 – 185 Hz Male 62
True Male 110 186 – 250 Hz 75 – 185 Hz Male 63
True Male 104 186 – 250 Hz 75 – 185 Hz Male 64
True Male 70 186 – 250 Hz 75 – 185 Hz Male 65
True Male 86 186 – 250 Hz 75 – 185 Hz Male 66
True Male 127 186 – 250 Hz 75 – 185 Hz Male 67
True Male 91 186 – 250 Hz 75 – 185 Hz Male 68
True Male 163 186 – 250 Hz 75 – 185 Hz Male 69
True Male 77 186 – 250 Hz 75 – 185 Hz Male 70
True Male 164 186 – 250 Hz 75 – 185 Hz Male 71
True Male 150 186 – 250 Hz 75 – 185 Hz Male 72
True Male 111 186 – 250 Hz 75 – 185 Hz Male 73
True Male 125 186 – 250 Hz 75 – 185 Hz Male 74
True Male 161 186 – 250 Hz 75 – 185 Hz Male 75
True Male 149 186 – 250 Hz 75 – 185 Hz Male 76
True Male 109 186 – 250 Hz 75 – 185 Hz Male 77
True Male 114 186 – 250 Hz 75 – 185 Hz Male 78
True Male 127 186 – 250 Hz 75 – 185 Hz Male 79
True Male 135 186 – 250 Hz 75 – 185 Hz Male 80
True Male 140 186 – 250 Hz 75 – 185 Hz Male 81
True Male 158 186 – 250 Hz 75 – 185 Hz Male 82
True Male 145 186 – 250 Hz 75 – 185 Hz Male 83
True Male 163 186 – 250 Hz 75 – 185 Hz Male 84
True Male 73 186 – 250 Hz 75 – 185 Hz Male 85
True Male 159 186 – 250 Hz 75 – 185 Hz Male 86
True Male 144 186 – 250 Hz 75 – 185 Hz Male 87
True Male 162 186 – 250 Hz 75 – 185 Hz Male 88
True Male 100 186 – 250 Hz 75 – 185 Hz Male 89
True Male 115 186 – 250 Hz 75 – 185 Hz Male 90
True Male 103 186 – 250 Hz 75 – 185 Hz Male 91
True Male 85 186 – 250 Hz 75 – 185 Hz Male 92
True Male 74 186 – 250 Hz 75 – 185 Hz Male 93
True Male 113 186 – 250 Hz 75 – 185 Hz Male 94
True Male 133 186 – 250 Hz 75 – 185 Hz Male 95
True Male 139 186 – 250 Hz 75 – 185 Hz Male 96
True Male 163 186 – 250 Hz 75 – 185 Hz Male 97
True Male 161 186 – 250 Hz 75 – 185 Hz Male 98
True Male 108 186 – 250 Hz 75 – 185 Hz Male 99
True Male 128 186 – 250 Hz 75 – 185 Hz Male 100
True Male 76 186 – 250 Hz 75 – 185 Hz Male 101
True Male 89 186 – 250 Hz 75 – 185 Hz Male 102
True Male 122 186 – 250 Hz 75 – 185 Hz Male 103
True Male 142 186 – 250 Hz 75 – 185 Hz Male 104
True Male 128 186 – 250 Hz 75 – 185 Hz Male 105
True Male 110 186 – 250 Hz 75 – 185 Hz Male 106
True Male 95 186 – 250 Hz 75 – 185 Hz Male 107
True Male 114 186 – 250 Hz 75 – 185 Hz Male 108
True Male 160 186 – 250 Hz 75 – 185 Hz Male 109
True Male 157 186 – 250 Hz 75 – 185 Hz Male 110
True Male 133 186 – 250 Hz 75 – 185 Hz Male 111
True Male 122 186 – 250 Hz 75 – 185 Hz Male 112
True Male 137 186 – 250 Hz 75 – 185 Hz Male 113
True Male 155 186 – 250 Hz 75 – 185 Hz Male 114
True Male 109 186 – 250 Hz 75 – 185 Hz Male 115
True Male 150 186 – 250 Hz 75 – 185 Hz Male 116
True Male 79 186 – 250 Hz 75 – 185 Hz Male 117
True Male 124 186 – 250 Hz 75 – 185 Hz Male 118
True Male 131 186 – 250 Hz 75 – 185 Hz Male 119
True Male 130 186 – 250 Hz 75 – 185 Hz Male 120
True Male 99 186 – 250 Hz 75 – 185 Hz Male 121
True Male 105 186 – 250 Hz 75 – 185 Hz Male 122
True Male 112 186 – 250 Hz 75 – 185 Hz Male 123
True Male 137 186 – 250 Hz 75 – 185 Hz Male 124
True Male 163 186 – 250 Hz 75 – 185 Hz Male 125
True Male 125 186 – 250 Hz 75 – 185 Hz Male 126
True Male 88 186 – 250 Hz 75 – 185 Hz Male 127
True Male 128 186 – 250 Hz 75 – 185 Hz Male 128
True Male 75 186 – 250 Hz 75 – 185 Hz Male 129
True Male 81 186 – 250 Hz 75 – 185 Hz Male 130
True Male 129 186 – 250 Hz 75 – 185 Hz Male 131
True Male 154 186 – 250 Hz 75 – 185 Hz Male 132
True Male 161 186 – 250 Hz 75 – 185 Hz Male 133
True Male 120 186 – 250 Hz 75 – 185 Hz Male 134
True Male 111 186 – 250 Hz 75 – 185 Hz Male 135
True Male 101 186 – 250 Hz 75 – 185 Hz Male 136
True Male 89 186 – 250 Hz 75 – 185 Hz Male 137
True Male 131 186 – 250 Hz 75 – 185 Hz Male 138
True Male 95 186 – 250 Hz 75 – 185 Hz Male 139
True Male 121 186 – 250 Hz 75 – 185 Hz Male 140
True Male 127 186 – 250 Hz 75 – 185 Hz Male 141
True Male 163 186 – 250 Hz 75 – 185 Hz Male 142
True Male 151 186 – 250 Hz 75 – 185 Hz Male 143
True Male 142 186 – 250 Hz 75 – 185 Hz Male 144
True Male 110 186 – 250 Hz 75 – 185 Hz Male 145
True Male 93 186 – 250 Hz 75 – 185 Hz Male 146
True Male 128 186 – 250 Hz 75 – 185 Hz Male 147
True Male 130 186 – 250 Hz 75 – 185 Hz Male 148
True Male 164 186 – 250 Hz 75 – 185 Hz Male 149
True Male 112 186 – 250 Hz 75 – 185 Hz Male 150
True Female 250 186 – 250 Hz 75 – 185 Hz Female 151
True Female 205 186 – 250 Hz 75 – 185 Hz Female 152
True Female 250 186 – 250 Hz 75 – 185 Hz Female 153
True Female 242 186 – 250 Hz 75 – 185 Hz Female 154
True Female 235 186 – 250 Hz 75 – 185 Hz Female 155
True Female 211 186 – 250 Hz 75 – 185 Hz Female 156
True Female 222 186 – 250 Hz 75 – 185 Hz Female 157
True Female 211 186 – 250 Hz 75 – 185 Hz Female 158
True Female 222 186 – 250 Hz 75 – 185 Hz Female 159
False Male 167 186 – 250 Hz 75 – 185 Hz Female 160
True Female 229 186 – 250 Hz 75 – 185 Hz Female 161
True Female 250 186 – 250 Hz 75 – 185 Hz Female 162
True Female 211 186 – 250 Hz 75 – 185 Hz Female 163
True Female 229 186 – 250 Hz 75 – 185 Hz Female 164
True Female 195 186 – 250 Hz 75 – 185 Hz Female 165
True Female 200 186 – 250 Hz 75 – 185 Hz Female 166
True Female 220 186 – 250 Hz 75 – 185 Hz Female 167
True Female 190 186 – 250 Hz 75 – 185 Hz Female 168
True Female 214 186 – 250 Hz 75 – 185 Hz Female 169
True Female 250 186 – 250 Hz 75 – 185 Hz Female 170
True Female 199 186 – 250 Hz 75 – 185 Hz Female 171
True Female 203 186 – 250 Hz 75 – 185 Hz Female 172
True Female 223 186 – 250 Hz 75 – 185 Hz Female 173
True Female 234 186 – 250 Hz 75 – 185 Hz Female 174
True Female 197 186 – 250 Hz 75 – 185 Hz Female 175
True Female 188 186 – 250 Hz 75 – 185 Hz Female 176
True Female 209 186 – 250 Hz 75 – 185 Hz Female 177
True Female 222 186 – 250 Hz 75 – 185 Hz Female 178
True Female 236 186 – 250 Hz 75 – 185 Hz Female 179
True Female 194 186 – 250 Hz 75 – 185 Hz Female 180
True Female 205 186 – 250 Hz 75 – 185 Hz Female 181
True Female 188 186 – 250 Hz 75 – 185 Hz Female 182
True Female 224 186 – 250 Hz 75 – 185 Hz Female 183
True Female 249 186 – 250 Hz 75 – 185 Hz Female 184
True Female 242 186 – 250 Hz 75 – 185 Hz Female 185
True Female 233 186 – 250 Hz 75 – 185 Hz Female 186
True Female 205 186 – 250 Hz 75 – 185 Hz Female 187
True Female 200 186 – 250 Hz 75 – 185 Hz Female 188
True Female 187 186 – 250 Hz 75 – 185 Hz Female 189
True Female 195 186 – 250 Hz 75 – 185 Hz Female 190
True Female 213 186 – 250 Hz 75 – 185 Hz Female 191
True Female 250 186 – 250 Hz 75 – 185 Hz Female 192
True Female 200 186 – 250 Hz 75 – 185 Hz Female 193
True Female 231 186 – 250 Hz 75 – 185 Hz Female 194
True Female 241 186 – 250 Hz 75 – 185 Hz Female 195
True Female 219 186 – 250 Hz 75 – 185 Hz Female 196
True Female 210 186 – 250 Hz 75 – 185 Hz Female 197
True Female 201 186 – 250 Hz 75 – 185 Hz Female 198
True Female 195 186 – 250 Hz 75 – 185 Hz Female 199
True Female 199 186 – 250 Hz 75 – 185 Hz Female 200
True Female 220 186 – 250 Hz 75 – 185 Hz Female 201
True Female 214 186 – 250 Hz 75 – 185 Hz Female 202
True Female 235 186 – 250 Hz 75 – 185 Hz Female 203
True Female 228 186 – 250 Hz 75 – 185 Hz Female 204
True Female 204 186 – 250 Hz 75 – 185 Hz Female 205
True Female 191 186 – 250 Hz 75 – 185 Hz Female 206
True Female 891 186 – 250 Hz 75 – 185 Hz Female 207
True Female 211 186 – 250 Hz 75 – 185 Hz Female 208
True Female 200 186 – 250 Hz 75 – 185 Hz Female 209
True Female 195 186 – 250 Hz 75 – 185 Hz Female 210
True Female 231 186 – 250 Hz 75 – 185 Hz Female 211
True Female 249 186 – 250 Hz 75 – 185 Hz Female 212
True Female 212 186 – 250 Hz 75 – 185 Hz Female 213
True Female 208 186 – 250 Hz 75 – 185 Hz Female 214
True Female 202 186 – 250 Hz 75 – 185 Hz Female 215
True Female 196 186 – 250 Hz 75 – 185 Hz Female 216
True Female 186 186 – 250 Hz 75 – 185 Hz Female 217
True Female 211 186 – 250 Hz 75 – 185 Hz Female 218
True Female 202 186 – 250 Hz 75 – 185 Hz Female 219
True Female 233 186 – 250 Hz 75 – 185 Hz Female 220
True Female 195 186 – 250 Hz 75 – 185 Hz Female 221
True Female 250 186 – 250 Hz 75 – 185 Hz Female 222
True Female 224 186 – 250 Hz 75 – 185 Hz Female 223
True Female 213 186 – 250 Hz 75 – 185 Hz Female 224
True Female 191 186 – 250 Hz 75 – 185 Hz Female 225
True Female 203 186 – 250 Hz 75 – 185 Hz Female 226
True Female 214 186 – 250 Hz 75 – 185 Hz Female 227
True Female 244 186 – 250 Hz 75 – 185 Hz Female 228
True Female 249 186 – 250 Hz 75 – 185 Hz Female 229
True Female 187 186 – 250 Hz 75 – 185 Hz Female 230
True Female 212 186 – 250 Hz 75 – 185 Hz Female 231
True Female 227 186 – 250 Hz 75 – 185 Hz Female 232
True Female 239 186 – 250 Hz 75 – 185 Hz Female 233
True Female 225 186 – 250 Hz 75 – 185 Hz Female 234
True Female 195 186 – 250 Hz 75 – 185 Hz Female 235
True Female 191 186 – 250 Hz 75 – 185 Hz Female 236
True Female 198 186 – 250 Hz 75 – 185 Hz Female 237
True Female 201 186 – 250 Hz 75 – 185 Hz Female 238
True Female 238 186 – 250 Hz 75 – 185 Hz Female 239
True Female 200 186 – 250 Hz 75 – 185 Hz Female 240
True Female 250 186 – 250 Hz 75 – 185 Hz Female 241
True Female 216 186 – 250 Hz 75 – 185 Hz Female 242
True Female 222 186 – 250 Hz 75 – 185 Hz Female 243
True Female 248 186 – 250 Hz 75 – 185 Hz Female 244
True Female 200 186 – 250 Hz 75 – 185 Hz Female 245
True Female 214 186 – 250 Hz 75 – 185 Hz Female 246
True Female 234 186 – 250 Hz 75 – 185 Hz Female 247
True Female 249 186 – 250 Hz 75 – 185 Hz Female 248
True Female 229 186 – 250 Hz 75 – 185 Hz Female 249
True Female 230 186 – 250 Hz 75 – 185 Hz Female 250
True Female 222 186 – 250 Hz 75 – 185 Hz Female 251
True Female 198 186 – 250 Hz 75 – 185 Hz Female 252
True Female 202 186 – 250 Hz 75 – 185 Hz Female 253
True Female 238 186 – 250 Hz 75 – 185 Hz Female 254
True Female 250 186 – 250 Hz 75 – 185 Hz Female 255
True Female 224 186 – 250 Hz 75 – 185 Hz Female 256
True Female 195 186 – 250 Hz 75 – 185 Hz Female 257
True Female 212 186 – 250 Hz 75 – 185 Hz Female 258
True Female 221 186 – 250 Hz 75 – 185 Hz Female 259
True Female 247 186 – 250 Hz 75 – 185 Hz Female 260
True Female 208 186 – 250 Hz 75 – 185 Hz Female 261
True Female 241 186 – 250 Hz 75 – 185 Hz Female 262
True Female 187 186 – 250 Hz 75 – 185 Hz Female 263
True Female 191 186 – 250 Hz 75 – 185 Hz Female 264
True Female 200 186 – 250 Hz 75 – 185 Hz Female 265
True Female 239 186 – 250 Hz 75 – 185 Hz Female 266
True Female 202 186 – 250 Hz 75 – 185 Hz Female 267
True Female 210 186 – 250 Hz 75 – 185 Hz Female 268
True Female 233 186 – 250 Hz 75 – 185 Hz Female 269
True Female 241 186 – 250 Hz 75 – 185 Hz Female 270
True Female 230 186 – 250 Hz 75 – 185 Hz Female 271
True Female 201 186 – 250 Hz 75 – 185 Hz Female 272
True Female 195 186 – 250 Hz 75 – 185 Hz Female 273
True Female 211 186 – 250 Hz 75 – 185 Hz Female 274
True Female 218 186 – 250 Hz 75 – 185 Hz Female 275
True Female 206 186 – 250 Hz 75 – 185 Hz Female 276
True Female 235 186 – 250 Hz 75 – 185 Hz Female 277
True Female 217 186 – 250 Hz 75 – 185 Hz Female 278
True Female 221 186 – 250 Hz 75 – 185 Hz Female 279
True Female 250 186 – 250 Hz 75 – 185 Hz Female 280
True Female 199 186 – 250 Hz 75 – 185 Hz Female 281
True Female 185 186 – 250 Hz 75 – 185 Hz Female 282
True Female 208 186 – 250 Hz 75 – 185 Hz Female 283
True Female 200 186 – 250 Hz 75 – 185 Hz Female 284
True Female 219 186 – 250 Hz 75 – 185 Hz Female 285
True Female 229 186 – 250 Hz 75 – 185 Hz Female 286
True Female 232 186 – 250 Hz 75 – 185 Hz Female 287
True Female 244 186 – 250 Hz 75 – 185 Hz Female 288
True Female 248 186 – 250 Hz 75 – 185 Hz Female 289
True Female 188 186 – 250 Hz 75 – 185 Hz Female 290
True Female 250 186 – 250 Hz 75 – 185 Hz Female 291
True Female 220 186 – 250 Hz 75 – 185 Hz Female 292
True Female 213 186 – 250 Hz 75 – 185 Hz Female 293
True Female 227 186 – 250 Hz 75 – 185 Hz Female 294
True Female 243 186 – 250 Hz 75 – 185 Hz Female 295
True Female 204 186 – 250 Hz 75 – 185 Hz Female 296
True Female 234 186 – 250 Hz 75 – 185 Hz Female 297
True Female 229 186 – 250 Hz 75 – 185 Hz Female 298
True Female 212 186 – 250 Hz 75 – 185 Hz Female 299
True Female 200 186 – 250 Hz 75 – 185 Hz Female 300

Table 2: shows frequency and percent of health and positive samples.

Frequency Percent
Male 148 43.30%
False parcent for male 2 6.6%
Female 149 46.70%
False Percent

For female

 1 3%
Total 300 100%

4. Conclusions:

Recently, the importance of sound in practical life has emerged as it enters into many fields, and the science of sound is a modern and developed science, and many are still seeking to delve into this science because of its importance. Reaching this In developing this field, we encountered some difficulties in collecting information on the subject of the research, but, thank God, the system was implemented and implemented successfully.

5.Future work:

Some ideas are provided in this paper for future work. Future work is some suggestions to improve the proposed approach to female voice ordering, and to improve a new technique for classification.

Finally, the proposed technique is applied to male and female voices, with the exception of children’s voices because the results were inaccurate because the frequency of their voices was too high..

6. Results:

  • Success rating for both sexes by sound
  • The system was tested on 30 male and female samples, and the system test success rate was the same, while the error rate was
  • Noise, noise, and microphone quality directly affect the rating system results, leading to inaccurate results
  • The more noise and distortion the recorded audio signal is, the more accurate the results will be
  • The efficiency of the autocorrelation technique in calculating the value of the signal frequency

7. Discussion:

Using a wide variety of human voices from the target group gives better results and better evaluation of the system, In this system, how much is targeting the adult group to classify them, so we recommend developing the system by integrating a set of mechanisms to be able to classify the age groups as a whole,Taking into account the recording of sounds in places free from noise and noise, and the use of a high-quality and sensitive microphone in picking up sounds with high accuracy so that the results are more accurate

8.References:

(40). Livieris, I. E., Pintelas, E., & Pintelas, P. (2019). Gender recognition by voice using an improved self-labeled algorithm. Machine Learning and Knowledge Extraction, 1(1), 492–503.

(41). Keyvanrad, M. A., & Homayounpour, M. M. (2010, May). Improvement on automatic speaker gender identification using classifier fusion. In 2010 18th Iranian conference on electrical engineering (pp. 538–541). IEEE.

(42). Alsulaiman, M., Ali, Z., & Muhammad, G. (2011, November). Gender classification with voice intensity. In 2011 UKSim 5th European symposium on computer modeling and simulation (pp. 205–209). IEEE.

(43). Chaudhary, S., & Sharma, D. K. (2018, October). Gender identification based on voice signal characteristics. In 2018 International conference on advances in computing, communication control and networking (ICACCCN) (pp. 869–874). IEEE.

(44). Pahwa, A., & Aggarwal, G. (2016). Speech feature extraction for gender recognition. International Journal of Image, Graphics and Signal Processing, 8(9), 17.

(45). I.R. Titze ,Physiologic and acoustic differences between male and female voices,The Journal of the Acoustical Society of America, 85 (4) (1989), pp. 1699-1707

(46). T.F. Cleveland,Acoustic properties of voice timbre types and their influence on voice classification,The Journal of the Acoustical Society of America, 61 (6) (1977), pp. 1622-1629

(47). Barkana, B.D., Zhou, J.. A new pitch-range based feature set for a speaker’s age and gender classification. Applied Acoustics 2015; 98:52–61

(48). Jayasankar, T., Vinothkumar, K., Vijayaselvi, A.. Automatic gender identification in speech recognition by genetic algorithm. Applied Mathematics and Information Sciences 2017

(49). A. Raahul, R. Sapthagiri, K. Pankaj, V. VijayarajanVoice based gender classification using machine learning Materials Science and Engineering Conference Series, 263 (2017), p. 042083

(50). Becker, K.. Gender recognition by voice and speech analysis. https://github.com/primaryobjects/voice-gender; 2019.