{"title":"基于最优阈值的泰米尔口吃数据集语音能量规律分析","authors":"M. Manjutha, P. Subashini, M. Krishnaveni","doi":"10.1109/ISC246665.2019.9071726","DOIUrl":null,"url":null,"abstract":"All over the world millions of people were affected by speech disorders in which one of the significant speech disorders is stuttering. Over the past two decade immense number of research is going on in the field of fluency disorder, and still it is necessary to enhance the analysis of stuttering disorder regional-wise. The speech signal tempo will vary with each individual where the specific fluctuation in the velocity of stutter speech is typical and it is due to the intervals in the speech rate which has a significant difference in normal stuttered speech. In this paper, Regularity of Speech Energy (RSE) was analyzed as normal, moderate and severe through Tamil speaking stuttered dataset. The analysis was done based on the energy threshold obtained during the irregular release of energy which is henceforth analyzed using optimal thresholding based on Particle Swam optimization (PSO) and Synergistic Fibroblast optimization (SFO) techniques. In order to evaluate the experimental analysis on RSE, statistical measures such as mean, standard deviation, Mean Square Error (MSE) and Root Mean Square Error (RMSE) were calculated. The experimental results of analysis on RSE have proved that stuttered speaker’s signal releases low energy when compared to the normal speaker where the optimal threshold energy enhances the detection of hidden speech energy.","PeriodicalId":306836,"journal":{"name":"2019 IEEE International Smart Cities Conference (ISC2)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis on Regularity of Speech Energy based on Optimal Thresholding for Tamil Stuttering Dataset\",\"authors\":\"M. Manjutha, P. Subashini, M. Krishnaveni\",\"doi\":\"10.1109/ISC246665.2019.9071726\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"All over the world millions of people were affected by speech disorders in which one of the significant speech disorders is stuttering. Over the past two decade immense number of research is going on in the field of fluency disorder, and still it is necessary to enhance the analysis of stuttering disorder regional-wise. The speech signal tempo will vary with each individual where the specific fluctuation in the velocity of stutter speech is typical and it is due to the intervals in the speech rate which has a significant difference in normal stuttered speech. In this paper, Regularity of Speech Energy (RSE) was analyzed as normal, moderate and severe through Tamil speaking stuttered dataset. The analysis was done based on the energy threshold obtained during the irregular release of energy which is henceforth analyzed using optimal thresholding based on Particle Swam optimization (PSO) and Synergistic Fibroblast optimization (SFO) techniques. In order to evaluate the experimental analysis on RSE, statistical measures such as mean, standard deviation, Mean Square Error (MSE) and Root Mean Square Error (RMSE) were calculated. The experimental results of analysis on RSE have proved that stuttered speaker’s signal releases low energy when compared to the normal speaker where the optimal threshold energy enhances the detection of hidden speech energy.\",\"PeriodicalId\":306836,\"journal\":{\"name\":\"2019 IEEE International Smart Cities Conference (ISC2)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Smart Cities Conference (ISC2)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISC246665.2019.9071726\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Smart Cities Conference (ISC2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISC246665.2019.9071726","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
全世界数以百万计的人受到语言障碍的影响,其中最重要的语言障碍之一就是口吃。在过去的二十年里,人们对言语流利障碍进行了大量的研究,但仍有必要加强对区域口吃障碍的分析。言语信号的节奏因人而异,其中口吃言语速度的特定波动是典型的,这是由于言语速率的间隔在正常口吃言语中具有显著差异。本文通过泰米尔语口吃数据集,分析了正常、中度和重度三种语言能量的规律性。该分析是基于不规则能量释放过程中获得的能量阈值进行的,随后使用基于粒子游优化(PSO)和协同成纤维细胞优化(SFO)技术的最优阈值进行分析。为了评价RSE的实验分析结果,计算了均数、标准差、均方误差(mean Square Error, MSE)和均方根误差(Root mean Square Error, RMSE)等统计指标。RSE分析的实验结果证明,与正常说话人相比,口吃者信号释放的能量较低,最优阈值能量增强了对隐藏语音能量的检测。
Analysis on Regularity of Speech Energy based on Optimal Thresholding for Tamil Stuttering Dataset
All over the world millions of people were affected by speech disorders in which one of the significant speech disorders is stuttering. Over the past two decade immense number of research is going on in the field of fluency disorder, and still it is necessary to enhance the analysis of stuttering disorder regional-wise. The speech signal tempo will vary with each individual where the specific fluctuation in the velocity of stutter speech is typical and it is due to the intervals in the speech rate which has a significant difference in normal stuttered speech. In this paper, Regularity of Speech Energy (RSE) was analyzed as normal, moderate and severe through Tamil speaking stuttered dataset. The analysis was done based on the energy threshold obtained during the irregular release of energy which is henceforth analyzed using optimal thresholding based on Particle Swam optimization (PSO) and Synergistic Fibroblast optimization (SFO) techniques. In order to evaluate the experimental analysis on RSE, statistical measures such as mean, standard deviation, Mean Square Error (MSE) and Root Mean Square Error (RMSE) were calculated. The experimental results of analysis on RSE have proved that stuttered speaker’s signal releases low energy when compared to the normal speaker where the optimal threshold energy enhances the detection of hidden speech energy.