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    The effect of age and gender on the acoustic analysis of anxious sound
    (Inst Advanced Science Extension, 2016) Ozseven, Turgut; Dugenci, Muharrem; Doruk, Ali
    The aim of this study is to investigate the effects of age and gender in sound reflection of anxiety with acoustic analysis. In the study, 148 speech records that express the emotions of the actors as anxiety and neutral were used as the data set. PRAAT software is used for acoustic analysis. The ANOVA method was used to analyze the data. The according to the results of statistical analysis, gender and age increased the count of acoustic parameters that affected of anxiety. The standard deviation of F0 increased too much, jitter local and jitter rap increased mid-range and other parameters did not change when examined changes based gender. The mean of F0, shimmer apq3 and number of unvoiced frame decreased to mid-range, the standard deviation of F0 and jitter local increased too much, the standard deviation of F3 and jitter rap increased to mid-range and other parameters did not change when examined changes based age. The changes occurring in emotions cause changes in sound by affecting respiratory and muscle tension. The anxiety has been changed according to gender and age because the number of parameters in the analysis based on the gender and age is more. The gender causes change in the speed of glottic cycle and this change increases with anxiety. In addition, vocal cords by both male and female occur irregularities and this case also differs according to age. The irregularities in intensity of sound in lower ages are being further while the pauses in the conversation with advancing age are increasing. (C) 2016 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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    The effects of digital filters on acoustic parameters, gender, age and emotion
    (Pamukkale Univ, 2017) Ozseven, Turgut; Dugenci, Muharrem
    Acoustic sound analysis is used for decision making process performed feature extraction from sound signal in environments such as machine, human and underwater. The pitch, formants, jitter and shimmer of acoustic parameters are mostly used in sound analysis. All frequency bands of various sound signals obtained from environments is not available for every system. The low frequency component is used for emotion detection in the human voice. In addition, sound signal must be have unwanted noise due to both form of records and environment. The desired frequency band of sound signal can be obtained, processes such as noise reduction, echo reduction and sound quality improving are realized with the help of digital filters. The purpose of this study is to investigate the effects of low-pass, high-pass and band-pass filters on acoustics parameters depending on age, gender and emotion.
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    Face Recognition by Distance and Slope between Facial Landmarks
    (Ieee, 2017) Ozseven, Turgut; Dugenci, Muharrem
    Facial landmark is to be determined point by point of areas such as eyes, nose, mouth, eyebrows on the face. Facial recognition studies can be generally categorized into two categories, local and global. All of the faces are used in the global face recognition while the face domain is divided into subspaces in the local face recognition. In face recognition studies facial landmarks are used for facial recognition with detection of regions located at the face and image processing methods. In this study, face recognition has been successfully analyzed using distance and slope between facial landmarks. Analyzes were performed with both statistical and classifiers. According to the results obtained, the distance and slope between the 14 landmarks used in the study were found to be statistically significant in the facial recognition. In addition, the classification was performed with the help of these features and the highest success was found with 94.60% with MLP classifier. Obtained findings show the usability of the distance and slope between the landmarks in facial recognition.
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    SPeech ACoustic (SPAC): A novel tool for speech feature extraction and classification
    (Elsevier Sci Ltd, 2018) Ozseven, Turgut; Dugenci, Muharrem
    Background and objective: The acoustic analysis, an objective evaluation method, is used to determine the descriptive attributes of the voices. Although there are many tools available in the literature for acoustic analysis, these tools are separated by features such as ease of use, visual interface, and acoustic parameter library. In this work, we have developed a new toolbox named SPAC for extracting and simulating attributes from speech files. Methods: SPAC has a modular structure and user-friendly interface, which will make up for the shortcomings of existing vehicles. In addition, modules can be used independently of each other. With SPAC, about 723 attributes can be extracted from each voice file in 9 categories. A validation test was applied to verify the validity of the toolbox-derived attributes. When the validation test was performed, the attributes obtained with Praat and OpenSMILE were grouped as standard, the attributes obtained with SPAC as test data, and the general differences between the attributes were evaluated with mean square error and mean percentage error. In another method used for verification, the classification performance is tested using the SPAC-derived attributes for classification. Results: According to the validation test results, SPAC attributes differ between 0.2% and 9.7% compared to other toolboxes. According to the results of the classification test, the SPAC attribute clusters can identify each class and the classification success varies between 1% and 3% according to the attributes obtained from other toolboxes. As a result, the attributes obtained with SPAC accurately describe the voice data. Conclusions: SPAC's superiority over existing toolboxes is that it has an easy-to-use user-friendly interface, it is modular, allows graphical representation of results, includes classification module and allows to work with SPAC data or data obtained from different toolboxes. In addition, operations performed with other tools can be performed more easily with SPAC.
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    Voice Traces of Anxiety: Acoustic Parameters Affected by Anxiety Disorder
    (Polska Akad Nauk, Polish Acad Sciences, Inst Fundamental Tech Res Pas, 2018) Ozseven, Turgut; Dugenci, Muharrem; Doruk, Ali; Kahraman, Hilal I.
    Although the emotions and learning based on emotional reaction are individual-specific, the main features are consistent among all people. Depending on the emotional states of the persons, various physical and physiological changes can be observed in pulse and breathing, blood flow velocity, hormonal balance, sound properties, face expression and hand movements. The diversity, size and grade of these changes are shaped by different emotional states. Acoustic analysis, which is an objective evaluation method, is used to determine the emotional state of people's voice characteristics. In this study, the reflection of anxiety disorder in people's voices was investigated through acoustic parameters. The study is a case-control study in cross-sectional quality. Voice recordings were obtained from healthy people and patients. With acoustic analysis, 122 acoustic parameters were obtained from these voice recordings. The relation of these parameters to anxious state was investigated statistically. According to the results obtained, 42 acoustic parameters are variable in the anxious state. In the anxious state, the subglottic pressure increases and the vocalization of the vowels decreases. The MFCC parameter, which changes in the anxious state, indicates that people can perceive this situation while listening to the speech. It has also been shown that text reading is also effective in triggering the emotions. These findings show that there is a change in the voice in the anxious state and that the acoustic parameters are influenced by the anxious state. For this reason, acoustic analysis can be used as an expert decision support system for the diagnosis of anxiety.