46 research outputs found
The Economic and Financial Status of Older Americans: Trends and Prospects
The global financial crisis and ensuing Great Recession reduced the income and wealth of many families, but older families generally fared better than young and middle-aged families. The Federal Reserve’s Survey of Consumer Finances reveals that being young was a significant risk factor during the downturn, regardless of a family’s race, ethnicity, or education level. Among older families, those headed by someone 70 or over fared slightly better than those headed by someone between 62 and 69. Income and wealth also increased most strongly among older families during the two decades preceding the crisis. Part of the explanation for favorable income and wealth trends among currently living older Americans is a positive birth-year cohort effect. After controlling for a host of factors related to income and wealth, we find that cohorts born in the late 1930s and 1940s have experienced more favorable income and wealth trajectories over their life courses than earlier- or later-born cohorts. While it is too soon to know how cohorts born in recent decades will fare over their lifetimes, it appears that the median Baby Boomer (born in the 1950s and early 1960s) and median member of Generation X (born in the late 1960s and 1970s) are on track for lower income and wealth in older age than those born in the 1930s and 1940s, holding constant many factors other than when a person was born. *The views expressed here are those of the authors alone and do not necessarily represent those of the Federal Reserve Bank of St. Louis or the Federal Reserve System
Going back to the source: inverse filtering of the speech signal with ANNs
In this paper we present a new method transforming speech signals to voice source signals (VSS) using artificial neural networks (ANN). We will point out that the ANN mapping of speech signals into source signals is quite accurate, and most of the irregularities in the speech signal will lead to an irregularity in the source signal, produced by the ANN (ANN-VSS). We will show that the mapping of the ANN is robust with respect to untrained speakers, different recording conditions and facilities, and different vocabularies. We will also present preliminary results which show that from the ANN source signal pitch periods can be determined accurately. (orig.)SIGLEAvailable from TIB Hannover: RR 5221(32)+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Forschung und Technologie (BMFT), Bonn (Germany)DEGerman
Combining Phase Identification and Statistic Modeling for Automated Parallel Benchmark Generation
Pitch determination considering laryngealization effects in spoken dialogs
A frequent phenomenon in spoken dialogs of the information seeking type are short elliptic utterances whose mood (declarative or interrogative) can only be distinguished by intonation. The main acoustic evidence is conveyed by the fundamental frequency or F_0-contour. Many algorithms for F_0 determination have been reported in the literature. A common problem are irregularities of speech known as 'laryngealizations'. This article describes an approach based on neural network techniques for the improved determination of fundamental frequency. First, an improved version of our neural network algorithm for reconstruction of the voice source signal (glottis signal) is presented. Second, the reconstructed voice source signal is used as input to another neural network distinguishing the three classes 'voiceless', 'voiced non-laryngealized', and 'voiced laryngealized'. Third, the results are used to improve an existing F_0 algorithm. Results of this approach are presented and discussed in the context of the application in a spoken dialog system. (orig.)SIGLEAvailable from TIB Hannover: RR 5221(33)+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Forschung und Technologie (BMFT), Bonn (Germany)DEGerman