A Cognitive Model to Mimic an Aspect of Low Level Perception of Sound: Modelling Reverberation Perception by Statistical Signal Analysis

2011 ◽  
Author(s):  
Francis F. Li
Keyword(s):  
Signal Analysis ◽  
Cognitive Model ◽  
Low Level ◽  
Statistical Signal Analysis

scholarly journals Измерение расстояния между излучателем и приемником в беспроводном канале связи при помощи сверхширокополосных хаотических радиоимпульсов

2019 ◽  
Vol 45 (17) ◽  
pp. 3
Author(s):  
Е.В. Ефремова ◽  
А.С. Дмитриев ◽  
Л.В. Кузьмин
Keyword(s):  
Signal Analysis ◽  
Distance Measurement ◽  
Statistical Signal Analysis

The possibility of wireless distance measurement using UWB chaotic radio pulses based on statistical signal analysis is considered. The results of experimental approbation of the proposed approach are given.

ECG/VCG Rhythm Diagnosis Using Statistical Signal Analysis-I. Identification of Persistent Rhythms

1978 ◽  
Vol BME-25 (4) ◽  
pp. 344-353 ◽  
Author(s):  
Donald E. Gustafson ◽  
Alan S. Willsky ◽  
Jyh-Yun Wang ◽  
Malcolm C. Lancaster ◽  
John H. Triebwasser
Keyword(s):  
Signal Analysis ◽  
Statistical Signal Analysis

scholarly journals Application of gamma densitometry and statistical signal analysis to gas phase velocity measurements in pipeline hydrotransport

2015 ◽  
Vol 92 ◽  
pp. 02122 ◽  
Author(s):  
Marcin Zych ◽  
Robert Hanus ◽  
Leszek Petryka ◽  
Dariusz Świsulski ◽  
Anna Strzępowicz ◽  
...  
Keyword(s):  
Phase Velocity ◽  
Gas Phase ◽  
Signal Analysis ◽  
Velocity Measurements ◽  
Statistical Signal Analysis

ECG/VCG Rhythm Diagnosis Using Statistical Signal Analysis-II. Identification of Transient Rhythms

1978 ◽  
Vol BME-25 (4) ◽  
pp. 353-361 ◽  
Author(s):  
Donald E. Gustafson ◽  
Alan S. Willsky ◽  
Iyh-Yun Wang ◽  
Malcolm C. Lancaster ◽  
John H. Triebwasser
Keyword(s):  
Signal Analysis ◽  
Statistical Signal Analysis

scholarly journals Evaluating Low-Level Speech Features Against Human Perceptual Data

2017 ◽  
Vol 5 ◽  
pp. 425-440 ◽  
Author(s):  
Caitlin Richter ◽  
Naomi H. Feldman ◽  
Harini Salgado ◽  
Aren Jansen
Keyword(s):  
Speech Perception ◽  
Cognitive Model ◽  
Human Perception ◽  
Speaker Normalization ◽  
Low Level ◽  
Human Data ◽  
Normalization Methods ◽  
Speech Features ◽  
New Framework ◽  
Better Than

We introduce a method for measuring the correspondence between low-level speech features and human perception, using a cognitive model of speech perception implemented directly on speech recordings. We evaluate two speaker normalization techniques using this method and find that in both cases, speech features that are normalized across speakers predict human data better than unnormalized speech features, consistent with previous research. Results further reveal differences across normalization methods in how well each predicts human data. This work provides a new framework for evaluating low-level representations of speech on their match to human perception, and lays the groundwork for creating more ecologically valid models of speech perception.

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