scholarly journals Latent factor analysis for synthesized speech quality-of-experience assessment

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Rishabh Gupta ◽  
Tiago H. Falk
Keyword(s):  
Factor Analysis ◽  
Quality Of Experience ◽  
Speech Quality ◽  
Latent Factor ◽  
Synthesized Speech

scholarly journals Review of recent standardization activities in speech quality of experience

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Sebastian Möller ◽  
Friedemann Köster
Keyword(s):  
Quality Of Experience ◽  
Speech Quality

Order-Variable Multi-Pulses Linear Prediction Speech Coding

2010 ◽  
Vol 44-47 ◽  
pp. 3672-3676
Author(s):  
Jian Lei Li ◽  
Zhen Ma ◽  
Ming Zhao Wu
Keyword(s):  
Speech Coding ◽  
Linear Prediction ◽  
Speech Quality ◽  
Variable Model ◽  
Synthesized Speech ◽  
Order Variable

On the base of all-poles model, this paper provides order-variable all-poles model according to instability of track complexity and applies this model in Multi-pulses linear prediction speech coding. This method is simulated in Matlab and quality of synthesized speech is evaluated, order-variable model is founded to keep better speech quality on the base of decreasing coding rates.

scholarly journals Procedures Used in Developing and Validating the Quality of Life Scale in the Context of the Ethno-Political Conflicts in Mathare and Kibra, Nairobi City County, Kenya

2020 ◽  
Vol 2 (2) ◽  
pp. 31-42
Author(s):  
Justus K. Musya
Keyword(s):  
Quality Of Life ◽  
Factor Analysis ◽  
Ethnic Groups ◽  
Latent Factor ◽  
Political Conflicts ◽  
Ethnopolitical Conflict ◽  
Quality Of Life Scale ◽  
Life Scale ◽  
History Of

Slight differences in standard of living, issuing from horizontal inequalities between ethnic groups, are a predicate of ethnopolitical violence in Kenya. Developing and validating a scale to estimate the quality of life differences, between warring ethnic groups, can deepen our understanding of an important precursor of ethnopolitical conflict. From a careful review of poverty and developmental literature, the 16 items used in the Quality of Life Scale emerged. In subsequent exploratory factor analysis, a three-factor solution surfaced, and this was subjected to confirmatory factor analysis (CFA). The CFA model scale met the criteria for composite reliability, construct validity, and strict factorial invariance. The scale has enriched our understanding of the three latent dimensions of quality of life that matter most in characterizing the quality of life. First, the indicator "proud about your life" was the strongest factor for latent factor social and physical wellbeing. Second, “can save income”, a proxy for quality of employment. This was the leading indicator for latent factor disposable income. Third, and the indicator “house comfortable to live in” was the notable indicator of latent factor living standards. The Quality of Life Scale can track trends in quality of life of ethnic groups that have a history of ethnopolitical conflict in places like Mathare and Kibra. The scale can be used in other known hotspots of violence in Kenya too where ethnic groups are susceptible to ethnopolitical conflict borne of quality of life differences.

scholarly journals Predicting the Quality of Synthesized and Natural Speech Impaired by Packet Loss and Coding Using PESQ and P.563 Models

2011 ◽  
Vol 97 (5) ◽  
pp. 852-868 ◽  
Author(s):  
Peter Počta ◽  
Jan Holub
Keyword(s):  
Packet Loss ◽  
Speech Quality ◽  
The Other ◽  
Natural Speech ◽  
Text To Speech ◽  
Synthesized Speech ◽  
Subjective Assessments ◽  
Almost All ◽  
The Impact

This paper investigates the impact of independent and dependent losses and coding on speech quality predictions provided by PESQ (also known as ITU-T P.862) and P.563 models, when both naturally-produced and synthesized speech are used. Two synthesized speech samples generated with two different Text-to-Speech systems and one naturally-produced sample are investigated. In addition, we assess the variability of PESQ's and P.563's predictions with respect to the type of speech used (naturally-produced or synthesized) and loss conditions as well as their accuracy, by comparing the predictions with subjective assessments. The results show that there is no difference between the impact of packet loss on naturally-produced speech and synthesized speech. On the other hand, the impact of coding is different for the two types of stimuli. In addition, synthesized speech seems to be insensitive to degradations provided by most of the codecs investigated here. The reasons for those findings are particularly discussed. Finally, it is concluded that both models are capable of predicting the quality of transmitted synthesized speech under the investigated conditions to a certain degree. As expected, PESQ achieves the best performance over almost all of the investigated conditions.

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

2019 ◽  
Vol 118 (1) ◽  
pp. 14-19
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Regression Analysis ◽  
Statistical Analysis ◽  
Correlation Analysis ◽  
Service Quality ◽  
Frequency Analysis ◽  
Primary Data ◽  
Exercise Intention

Background/Objectives: The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted amongst college students who have experiences in using exercise App(s) and regularly exercise. The questionnaire is composed of four parts asking about service quality, exercise commitment, continued exercise intention, which were measured with a 5-point Likert Scale, and demographics. Frequency analysis, factor analysis, correlation analysis, and regression analysis were carried out to analyze the obtained data with PASW 18.0.

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