Zero Frequency Filter Based Analysis of Voice Disorders

2017 ◽  
Author(s):  
Nagaraj Adiga ◽  
Vikram C.M. ◽  
Keerthi Pullela ◽  
S.R. Mahadeva Prasanna
Keyword(s):  
Voice Disorders ◽  
Frequency Filter ◽  
Zero Frequency

Early detection of bearing faults using minimum entropy deconvolution adjusted and zero frequency filter

2021 ◽  
pp. 107754632098636
Author(s):  
Keshav Kumar ◽  
Sumitra Shukla ◽  
Sachin K Singh
Keyword(s):  
Time Domain ◽  
Vibration Signal ◽  
Rolling Element Bearings ◽  
Frequency Filtering ◽  
Minimum Entropy ◽  
Frequency Filter ◽  
Rolling Element ◽  
Zero Frequency Filtering ◽  
Bearing Vibration ◽  
Zero Frequency

A method based on minimum entropy deconvolution with convolution adjustment and zero frequency filter is presented for the identification of weak faults in rolling element bearings. Localized fault present in rolling element bearings causes periodic impulses in the bearing vibration signal. The zero frequency filtering of the bearing vibration signal keeps only the localized disturbances at the impulse locations while attenuating the non-impulsive components of the signal. The effectiveness of zero frequency filtering depends on the strength of impulses present in the measured faulty bearing signal in time domain. In the present work, Minimum entropy deconvolution adjusted is used as a preprocessor to improve the strength of impulses in the measured time-domain bearing signal. The effectiveness of the proposed algorithm is tested with simulated signals for the faulty bearing vibration at different levels of added Gaussian noise. The algorithm is also validated using experimental bearing vibration dataset. Results from the proposed algorithm are compared with the results of the zero frequency filter and local mean subtraction-based technique for rolling element bearings’ fault identification. The proposed algorithm performs better detection in case of a weak fault signal.

A Simplified Realization of Zero Frequency Filter for Hardware Implementation

2020 ◽  
Vol 39 (9) ◽  
pp. 4717-4729
Author(s):  
Nagapuri Srinivas ◽  
Gayadhar Pradhan ◽  
D. Govind
Keyword(s):  
Hardware Implementation ◽  
Frequency Filter ◽  
Zero Frequency

Voice Activity Detection Algorithm Using Zero Frequency Filter Assisted Peaking Resonator and Empirical Mode Decomposition

2013 ◽  
Vol 22 (3) ◽  
pp. 269-282
Author(s):  
M.S. Rudramurthy ◽  
V. Kamakshi Prasad ◽  
R. Kumaraswamy
Keyword(s):  
White Noise ◽  
Empirical Mode Decomposition ◽  
Voice Activity Detection ◽  
Data Driven ◽  
Activity Detection ◽  
Frequency Filter ◽  
Source Information ◽  
Mode Decomposition ◽  
Voice Activity ◽  
Zero Frequency

AbstractIn this article, a new adaptive data-driven strategy for voice activity detection (VAD) using empirical mode decomposition (EMD) is proposed. Speech data are decomposed using an a posteriori, adaptive, data-driven EMD in the time domain to yield a set of physically meaningful intrinsic mode functions (IMFs). Each IMF preserves the nonlinear and nonstationary property of the speech utterance. Among a set of IMFs, the IMF that contains source information dominantly called characteristic IMF (CIMF) can be identified and extracted by designing a zero-frequency filter-assisted peaking resonator. The detected CIMF is used to compute energy using short-term processing. Choosing proper threshold, voiced regions in speech utterances are detected using frame energy. The proposed framework has been studied on both clean speech utterance and noisy speech utterance (0-dB white noise). The proposed method is used for voice activity detection (VAD) in the presence of white noise and shows encouraging result in the presence of white noise up to 0 dB.

An Investigation of Sex-Bias in Classroom Teachers' Speech and Language Referrals

1980 ◽  
Vol 11 (3) ◽  
pp. 169-174 ◽  
Author(s):  
Ellen Marie Silverman ◽  
Katherine Van Opens
Keyword(s):  
School Districts ◽  
Voice Disorders ◽  
Communication Disorders ◽  
Sixth Grade ◽  
Sex Bias ◽  
Classroom Teachers ◽  
Communication Disorder ◽  
Primary Procedure ◽  
Teacher Referrals ◽  
Grade Classroom

Kindergarten through sixth grade classroom teachers in four school districts completed questionnaires designed to determine whether they would be more likely to refer a boy than a girl with an identical communication disorder. The teachers were found to be equally likely to refer a girl as a boy who presented a disorder of articulation, language, or voice, but they were more likely to refer a boy for speech-language remediation who presented the disorder of stuttering. The tendency for the teachers to allow the sex of a child to influence their likelihood of referral for stuttering remediation, to overlook a sizeable percentage of children with chronic voice disorders, and to be somewhat inaccurate generally in their referrals suggests that teacher referrals are best used as an adjunct to screening rather than as a primary procedure to locate children with communication disorders.

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