Microprocessor-Based Speech Processing System

Durational measurements of frication, aspiration, prevoicing, and voice onset are often difficult to perform from the spectrogram, and the resolution is limited to about 5 ms. In many instances, a higher resolution can be obtained from a study of waveforms than from a study of spectrum. We present a microprocessor-based speech acquisition and processing system which uses waveform analysis techniques to extract measurements from the acoustic signal. The system is low cost and portable; it operates in "real time" and employs noninvasive data-capturing techniques. The usefulness of the system is demonstrated in the VOT measurement of CV clusters and in the measurement of fundamental frequency.

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Real-time multiprocessor speech processing system to aid the hearing impaired

10.1109/iembs.1989.96313 ◽

2003 ◽

Author(s):

G.C. Papagiannis ◽

H.C. Lee

Keyword(s):

Real Time ◽

Speech Processing ◽

Processing System ◽

Hearing Impaired

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ECOLOG II: a real-time acoustic signal processing system for fish stock assessment

Ultrasonics ◽

10.1016/0041-624x(90)90092-3 ◽

1990 ◽

Vol 28 (4) ◽

pp. 256-265 ◽

Cited By ~ 2

Author(s):

A. Stepnowski ◽

R.S. Mitchell

Keyword(s):

Signal Processing ◽

Real Time ◽

Acoustic Signal ◽

Stock Assessment ◽

Processing System ◽

Fish Stock ◽

Signal Processing System ◽

Fish Stock Assessment

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A real-time digital speech processing system for an auditory prosthesis

10.1109/icassp.1988.197149 ◽

2003 ◽

Author(s):

R.B. Knapp ◽

B. Townshend

Keyword(s):

Real Time ◽

Speech Processing ◽

Processing System ◽

Auditory Prosthesis ◽

Digital Speech Processing

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Evaluation of RapidScat Ocean Vector Winds for Data Assimilation and Reanalysis

Monthly Weather Review ◽

10.1175/mwr-d-17-0117.1 ◽

2018 ◽

Vol 146 (1) ◽

pp. 199-211 ◽

Cited By ~ 3

Author(s):

Will McCarty ◽

Mohar Chattopadhyay ◽

Austin Conaty

Keyword(s):

Real Time ◽

Forecast Error ◽

Low Cost ◽

Surface Wind ◽

Space Station ◽

Processing System ◽

Error Reduction ◽

Time Data ◽

Full Data ◽

The Impact

Abstract The Rapid Scatterometer (RapidScat) was built as a low-cost follow-on to the QuikSCAT mission. It flew on the International Space Station (ISS) and provided data from 3 October 2014 to 20 August 2016. These data allowed for the retrieval of surface wind vectors derived from surface roughness estimates measured from multiple coincident azimuth angles. These measurements were unique to the historical scatterometer record in that the ISS flies in a low inclination, non-sun-synchronous orbit. Scatterometry-derived wind vectors have been routinely assimilated in both forward processing and reanalysis systems run at the Global Modeling and Assimilation Office (GMAO). As the RapidScat retrievals were made available in near–real time, they were assimilated in the forward processing system, and the methods to assimilate and evaluate these retrievals are described. Time series of data statistics are presented first for the near-real-time data assimilated in GMAO forward processing. Second, the full data products provided by the RapidScat team are compared passively to the MERRA-2 reanalysis. Both sets of results show that the root-mean-square (RMS) difference of the observations and the GMAO model background fields increased over the course of the data record. Furthermore, the observations and the backgrounds are shown to be biased for both the zonal and meridional wind components. The retrievals are shown to have had a net forecast error reduction via the forecast sensitivity observation impact (FSOI) metric, which is a quantification of 24-h forecast error reduction, though the impact became neutral as the signal-to-noise ratio of the instrument decreased over its lifespan.

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Measurement System of Metal Magnetic Memory Method Signals around Rectangular Defects of a Ferromagnetic Pipe

Applied Sciences ◽

10.3390/app9132695 ◽

2019 ◽

Vol 9 (13) ◽

pp. 2695

Author(s):

J. Jesús Villegas-Saucillo ◽

José Javier Díaz-Carmona ◽

Carlos A. Cerón-Álvarez ◽

Raúl Juárez-Aguirre ◽

Saúl M. Domínguez-Nicolás ◽

...

Keyword(s):

Real Time ◽

Measurement System ◽

Oil And Gas ◽

Low Cost ◽

Processing System ◽

Magnetic Sensors ◽

Special Treatment ◽

Magnetic Memory ◽

Metal Magnetic Memory ◽

Real Time Monitoring

Oil and gas pipeline networks require the periodic inspection of their infrastructure, which can cause gas and oil leakage with several damages to the environment and human health. For this, non-destructive testing (NDT) techniques of low-cost and easy implementation are required. An option is the metal magnetic memory (MMM) method, which could be used for real-time monitoring defects of ferromagnetic structures based on the analysis of self-magnetic leakage fields distribution around each defect. This method only requires magnetic sensors with high resolution and a data processing system. We present a measurement system of tangential and normal MMM signals of three rectangular defects of an ASTM A-36 steel pipe. This system is formed by a magnetoresistive sensor, an Arduino nano and a virtual instrumentation. The measured magnetic signals have non-uniform distributions around the rectangular defects, which have small differences with respect to the results obtained of a 2D magnetic dipole model. The size of each rectangular defect is related to the amplitude and shape of its tangential and normal MMM signals. The proposed system could be used for real-time monitoring of the size and location of rectangular defects of ferromagnetic pipes. This system does not require expensive equipment, operators with high skill level or a special treatment of the ferromagnetic samples.

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