Effects of the Phonological Contents and Transmission Channels on Forensic Speaker Recognition

2011 ◽  
pp. 275-308 ◽  
Author(s):  
Kanae Amino ◽  
Takashi Osanai ◽  
Toshiaki Kamada ◽  
Hisanori Makinae ◽  
Takayuki Arai
Keyword(s):  
Speaker Recognition ◽  
Transmission Channels

Economic Significance of Social Capital

2011 ◽  
pp. 46-65 ◽  
Author(s):  
L. Polishchuk ◽  
R. Menyashev
Keyword(s):  
Social Capital ◽  
Collective Action ◽  
Common Good ◽  
Economic Conditions ◽  
Formal Institutions ◽  
Transmission Channels ◽  
Economic Significance ◽  
Bonding And Bridging ◽  
The Impact

The paper deals with economics of social capital which is defined as the capacity of society for collective action in pursuit of common good. Particular attention is paid to the interaction between social capital and formal institutions, and the impact of social capital on government efficiency. Structure of social capital and the dichotomy between its bonding and bridging forms are analyzed. Social capital measurement, its economic payoff, and transmission channels between social capital and economic outcomes are discussed. In the concluding section of the paper we summarize the results of our analysis of the role of social capital in economic conditions and welfare of Russian cities.

Speaker Identity Recognition by Acoustic and Visual Data Fusion through Personal Privacy for Smart Care and Service Applications

2020 ◽  
Vol 64 (4) ◽  
pp. 40404-1-40404-16
Author(s):  
I.-J. Ding ◽  
C.-M. Ruan
Keyword(s):  
Face Detection ◽  
Speaker Recognition ◽  
Visual Information ◽  
Classification Tree ◽  
Gaussian Mixture ◽  
Recognition Method ◽  
Indoor Space ◽  
Identity Recognition ◽  
Visual Identity ◽  
Speaker Classification

Abstract With rapid developments in techniques related to the internet of things, smart service applications such as voice-command-based speech recognition and smart care applications such as context-aware-based emotion recognition will gain much attention and potentially be a requirement in smart home or office environments. In such intelligence applications, identity recognition of the specific member in indoor spaces will be a crucial issue. In this study, a combined audio-visual identity recognition approach was developed. In this approach, visual information obtained from face detection was incorporated into acoustic Gaussian likelihood calculations for constructing speaker classification trees to significantly enhance the Gaussian mixture model (GMM)-based speaker recognition method. This study considered the privacy of the monitored person and reduced the degree of surveillance. Moreover, the popular Kinect sensor device containing a microphone array was adopted to obtain acoustic voice data from the person. The proposed audio-visual identity recognition approach deploys only two cameras in a specific indoor space for conveniently performing face detection and quickly determining the total number of people in the specific space. Such information pertaining to the number of people in the indoor space obtained using face detection was utilized to effectively regulate the accurate GMM speaker classification tree design. Two face-detection-regulated speaker classification tree schemes are presented for the GMM speaker recognition method in this study—the binary speaker classification tree (GMM-BT) and the non-binary speaker classification tree (GMM-NBT). The proposed GMM-BT and GMM-NBT methods achieve excellent identity recognition rates of 84.28% and 83%, respectively; both values are higher than the rate of the conventional GMM approach (80.5%). Moreover, as the extremely complex calculations of face recognition in general audio-visual speaker recognition tasks are not required, the proposed approach is rapid and efficient with only a slight increment of 0.051 s in the average recognition time.

New Feature Vectors using GFCC for Speaker Identification

2018 ◽  
Vol 6 (8) ◽  
pp. 243
Author(s):  
A. Nagesh
Keyword(s):  
Speaker Recognition ◽  
Speaker Identification ◽  
Signal To Noise Ratio ◽  
Main Idea ◽  
Extraction Methods ◽  
Identification System ◽  
Identification Performance ◽  
Feature Vectors ◽  
Overall Performance ◽  
New Feature

The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set of feature vectors using Gaussian Mixer model (GMM) for speaker identification. The MFCC are the default feature vectors for speaker recognition, but they are not very robust at the presence of additive noise. The GFCC features in recent studies have shown very good robustness against noise and acoustic change. The main idea is  GFCC features based on GMM feature extraction is to improve the overall speaker identification performance in low signal to noise ratio (SNR) conditions.

Tracking the Transmission Channels of Fiscal Deficit and Food Inflation Linkages: A Structural VAR Approach

2020 ◽  
pp. 165-172
Keyword(s):  
Positive Impact ◽  
Structural Var ◽  
Fiscal Deficit ◽  
Agricultural Industry ◽  
Vector Autoregressive ◽  
Transmission Channels ◽  
Government Deficit ◽  
Import And Export ◽  
The Impact ◽  
Food Inflation

This empirical analysis aspired to unearth the transmission channels of fiscal deficit and food inflation linkages in the Indian perspective by reasonably exerting the data for 1991 to 2017. The precise results of structural vector autoregressive (SVAR) analysis proffered that there were three different mechanisms of transmission such as consumption, general inflation, and import channels that led to food inflation in response to the high fiscal deficit. The first channel revealed that government deficit spending had a positive impact on income which further led to food inflation through surging the household consumption expenditure. It was concluded that fiscal deficit passed through general inflation finally leading to a food price surge in the economy and seemed to work as cost-push inflation for the food and agricultural industry. The outcome also revealed that the impact of fiscal deficit passed to food inflation through external linkages such as import and export.

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