01992nam a2200253   4500001000700000090001100007100004100018101000800059200014300067210002500210215002000235300014900255330099400404606003701398606002601435606002601461606002501487606002101512606001701533606002701550700003101577955001101608995011901619394577  a394577  a20170525d2017       y0pory50      ba  aeng  aA framework for performing forensic and investigatory speaker comparisons using automated methodsbRecurso eletrónicofDavid Brian Marks  aDenverc[s.n.]d2017  a1 CD-ROMd12 cm  aTese de Mestrado apresentada à Universidade do Colorado, tendo como orientadora Catalin Grigoras. Ficheiro de 2,99 MB em formato PDF (174 p.).  aI. INTRODUCTION. Terminology. Challenges of Voice Forensics. Scope. II. BACKGROUND. Scientific Foundations. The Scientific Method. Bias Effects. Legal Foundations. Rules of Evidence. Federal Case Law. State Case Law. Factors in Speaker Recognition. The Nature of the Human Voice. Speaker Recognition Systems. Bias Effects. Standards. Historical Baggage. III. COMPARISON FRAMEWORK. Case Assessment. Forensic Request. Administrative Assessment. Technical Assessment. Decision to Proceed with Analysis. Analysis and Processing. Data Preparation. Data Enhancement. Selection of the Relevant Population. System Performance and Calibration. Combining Results from Multiple Methods or Systems. Conclusions. Interpreting Results. Communicating Results. Case Studies. Case Study 1. Case Study 2. Case Study 3. SUMMARY AND CONCLUSIONS. Challenges in the Relevant Population. Fusion for Multiple Algorithms. Verbal Scale Standards for Reporting Results. Data and Standards for Validation. REFERENCES.  aIDENTIFICAÇÃO DA VOZ9345486  aEXAME À VOZ9346274  aREGISTO VOCAL9343486  aMETODOLOGIAS9341295  aSOFTWARE9235148  aTESE9334284  aESTADOS UNIDOS9334103  aMARKSbDavid Brian9358463  xOferta  104PJCD_284_00000000000000052022-06-066PJCD2849427214aPJcPJfPJ1CD284_109kPJCD284n2022-06-06o0rMOxOferta