By Kanae Amino Ph.D., Takashi Osanai Ph.D., Toshiaki Kamada B.E., Hisanori Makinae Ph.D. (auth.), Amy Neustein, Hemant A. Patil (eds.)
Forensic Speaker attractiveness: legislation Enforcement and Counter-Terrorism is an anthology of the study findings of 35 speaker popularity specialists from worldwide. the amount presents a multidimensional view of the advanced technology curious about settling on no matter if a suspect’s voice actually suits forensic speech samples, amassed by means of legislations enforcement and counter-terrorism enterprises, which are linked to the fee of a terrorist act or different crimes. whereas addressing such themes because the demanding situations of forensic case paintings, dealing with speech sign degradation, interpreting positive aspects of speaker popularity to optimize voice verification method functionality, and designing voice purposes that meet the sensible wishes of legislation enforcement and counter-terrorism corporations, this fabric all sounds a standard subject: how the trials of forensic software are challenging new degrees of excellence in all facets of speaker acceptance. The members are one of the most outstanding scientists in speech engineering and sign processing; and their paintings represents such various nations as Switzerland, Sweden, Italy, France, Japan, India and the United States.
Forensic Speaker Recognition is an invaluable publication for forensic speech scientists, speech sign processing specialists, speech process builders, felony prosecutors and counter-terrorism intelligence officials and agents.
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Additional info for Forensic Speaker Recognition: Law Enforcement and Counter-Terrorism
4 Processing chain for calculating between-sources similarity scores and their distribution lation) having voices similar to the trace, and, combined with the police investigation, to focus on and select a suspected speaker. The methodology presented needs three databases for the calculation and the interpretation of the evidence: the potential (relevant) population database (P), the suspected speaker reference database (R) and the suspected speaker control database (C) . The potential population database (P) is a database for modeling the variability of the speech of all the potential relevant sources, using the automatic speaker recognition method.
Forensic Linguist 4:18–28 59. Philippon AC, Cherryman J, Bull R, Vrij A (2007) Earwitness identification performances: the effect of language, target, deliberate strategies and indirect measures. Appl Cogn Psychol 21:539–550 60. Hashimoto M, Kitagawa S, Higuchi N (1998) Quantitative analysis of acoustic features affecting speaker identification. J Acoust Soc Jpn 54:169–178 61. Hollien H, Majewski W, Doherty TE (1982) Perceptual identification of voices under normal, stress, and disguise speaking conditions.
Kernel density estimation was used to calculate the probability densities of distribution of scores for each of the hypotheses.
Forensic Speaker Recognition: Law Enforcement and Counter-Terrorism by Kanae Amino Ph.D., Takashi Osanai Ph.D., Toshiaki Kamada B.E., Hisanori Makinae Ph.D. (auth.), Amy Neustein, Hemant A. Patil (eds.)