fletcher critical band

2011 ◽  
Keyword(s):  
Critical Band

Auditory Masking and the Critical Band

1961 ◽  
Vol 33 (4) ◽  
pp. 484-502 ◽  
Author(s):  
Donald D. Greenwood
Keyword(s):  
Critical Band ◽  
Auditory Masking

PROGRESS IN PHYSIOLOGICAL ACOUSTICS

2013 ◽  
Vol 13 (05) ◽  
pp. 1340007 ◽  
Author(s):  
FUYIN MA ◽  
JIU HUI WU ◽  
HAIYUN HOU
Keyword(s):  
Experimental Testing ◽  
Critical Band ◽  
Simulation Methods ◽  
Acoustic Model ◽  
Analysis Method ◽  
Biological Factors ◽  
Physical Acoustics ◽  
Physiological Acoustics ◽  
Numerical Simulation Methods ◽  
Evaluation Survey

Physiological acoustics is a very hot topic in modern acoustic research, which is to study the hearing mechanism and the utterance of both humans and animals. It could be divided into two main aspects: physical acoustics of the ear and physiological acoustics. In physiological acoustics, there are some common research methods, such as objective experimental testing, subjective feelings evaluation survey statistical method, building the physical acoustic model and numerical simulation methods, etc. The authors are researching the accurate mathematical model of equal loudness curves, critical band and masking effects, by applying the holographic concept with several biological factors which are required to build a standard model. The cochlear emission information should be extracted from wavelet analysis method and two hearing protection technologies are being developed by band shielding.

Complex tone processing in primary auditory cortex of the awake monkey. II. Pitch versus critical band representation

2000 ◽  
Vol 108 (1) ◽  
pp. 247-262 ◽  
Author(s):  
Yonatan I. Fishman ◽  
David H. Reser ◽  
Joseph C. Arezzo ◽  
Mitchell Steinschneider
Keyword(s):  
Auditory Cortex ◽  
Primary Auditory Cortex ◽  
Critical Band ◽  
Complex Tone ◽  
Awake Monkey

Emotion Recognition From Speech Using Perceptual Filter and Neural Network

2020 ◽  
pp. 78-91 ◽  
Author(s):  
Revathi A. ◽  
Sasikaladevi N.
Keyword(s):  
Neural Network ◽  
Emotion Recognition ◽  
Vector Quantization ◽  
Group Performance ◽  
Back Propagation ◽  
Critical Band ◽  
Emotion Classification ◽  
Back Propagation Algorithm ◽  
Propagation Algorithm ◽  
Speaker Independent

This chapter on multi speaker independent emotion recognition encompasses the use of perceptual features with filters spaced in Equivalent rectangular bandwidth (ERB) and BARK scale and vector quantization (VQ) classifier for classifying groups and artificial neural network with back propagation algorithm for emotion classification in a group. Performance can be improved by using the large amount of data in a pertinent emotion to adequately train the system. With the limited set of data, this proposed system has provided consistently better accuracy for the perceptual feature with critical band analysis done in ERB scale.

Sound‐quality diagnosis method of permanent magnet synchronous motor for electric vehicles based on critical band analysis

2019 ◽  
Vol 13 (10) ◽  
pp. 1613-1621
Author(s):  
Conggan Ma ◽  
Yuansheng An ◽  
Lantao Liu ◽  
Michele Degano ◽  
Xingjiang Ning ◽  
...  
Keyword(s):  
Permanent Magnet ◽  
Electric Vehicles ◽  
Permanent Magnet Synchronous Motor ◽  
Sound Quality ◽  
Synchronous Motor ◽  
Critical Band ◽  
Diagnosis Method ◽  
Quality Diagnosis
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