Combining evidences from mel cepstral, cochlear filter cepstral and instantaneous frequency features for detection of natural vs. spoofed speech

2015 ◽  
Author(s):  
Tanvina B. Patel ◽  
Hemant A. Patil
Keyword(s):  
Instantaneous Frequency ◽  
Frequency Features

Instantaneous Frequency Features for Noise Robust Speech Recognition

2019 ◽  
Author(s):  
Shekhar Nayak ◽  
Dhar B. Shashank ◽  
Saurabhchand Bhati ◽  
Koilakuntla Bramhendra ◽  
K. Sri Rama Murty
Keyword(s):  
Speech Recognition ◽  
Instantaneous Frequency ◽  
Robust Speech Recognition ◽  
Noise Robust Speech Recognition ◽  
Noise Robust ◽  
Frequency Features

scholarly journals Deep Recurrent Learning for Heart Sounds Segmentation based on Instantaneous Frequency Features

Elektron ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 52-57
Author(s):  
Alvaro Joaquin Gaona ◽  
Pedro David Arini
Keyword(s):  
Instantaneous Frequency ◽  
Short Term Memory ◽  
Heart Sounds ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
Para Determinar ◽  
Frequency Features

En este trabajo se presenta un conjunto de técnicas bien conocidas definiendo un método automático para determinar los sonidos fundamentales en un fonocardiograma (PCG). Mostraremos una red neuronal recurrente capaz de segmentar segmentar un fonocardiograma en sus principales componentes, y una forma muy específica de extraer frecuencias instantáneas que jugarán un importante rol en el entrenamiento y validación del modelo propuesto. Más específicamente, el método propuesto involucra una red neuronal Long Short-Term Memory (LSTM) acompañada de la Transformada Sincronizada de Fourier (FSST) usada para extraer atributos en tiempo-frecuencia en un PCG. El presente enfoque fue evaluado con señales de fonocardiogramas mayores a 5 segundos y menores a 35 segundos de duración extraı́dos de bases de datos públicas. Se demostró, que con una arquitectura relativamente pequeña, un conjunto de datos acotado y una buena elección de las características, este método alcanza una eficacia cercana a la del estado del arte, con una sensitividad promedio de 89.5%, una precisión promedio de 89.3% y una exactitud promedio de 91.3%.

scholarly journals Comparison of Frequency Features of Pulse Echoes from Different Reflectors

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Anatoly B. Rinkevich ◽  
Olga V. Nemytova ◽  
Dmitry V. Perov
Keyword(s):  
Instantaneous Frequency ◽  
Piezoelectric Transducer ◽  
Wavelet Transformation ◽  
Noise Immunity ◽  
Elastic Media ◽  
Frequency Determination ◽  
Pulse Echo ◽  
Frequency Features

The analysis of interaction of ultrasonic pulses with different reflectors which are located in elastic media is carried out. A parameter which allows estimating the form of reflector is instantaneous frequency of pulse-echo. This parameter is an unsteady pulse echo characteristic. Instantaneous frequency determination algorithm is to use wavelet transformation which has increased noise immunity. It is shown that the instantaneous frequency value for a pulse echo is often shifted from a rated frequency of piezoelectric transducer. Difference between the frequencies extensively depends on the reflector form.

Novel Variable Length Teager Energy Separation Based Instantaneous Frequency Features for Replay Detection

2017 ◽  
Author(s):  
Hemant A. Patil ◽  
Madhu R. Kamble ◽  
Tanvina B. Patel ◽  
Meet H. Soni
Keyword(s):  
Instantaneous Frequency ◽  
Variable Length ◽  
Energy Separation ◽  
Teager Energy ◽  
Frequency Features

Hilbert-Huang Transform Based Instantaneous Frequency Features for Underwater Voice (I) Transmission

2014 ◽  
pp. 305-310 ◽  
Author(s):  
C. F. Lin ◽  
K. J. Hsiao ◽  
C. C. Wen ◽  
S. H. Chang ◽  
I. A. Parinov
Keyword(s):  
Instantaneous Frequency ◽  
Hilbert Huang Transform ◽  
Frequency Features

Delivering Sustainable Water Systems Using Kalman Filter and Statistical Approach

2017 ◽  
Vol 4 (1) ◽  
pp. 41-52
Author(s):  
Dedy Loebis
Keyword(s):  
Kalman Filtering ◽  
Statistical Approach ◽  
Water Systems ◽  
Data Sets ◽  
Pressure Data ◽  
Burst Event ◽  
Sample Data ◽  
Other Information ◽  
Supply Systems ◽  
Frequency Features

This paper presents the results of work undertaken to develop and test contrasting data analysis approaches for the detection of bursts/leaks and other anomalies within wate r supply systems at district meter area (DMA)level. This was conducted for Yorkshire Water (YW) sample data sets from the Harrogate and Dales (H&D), Yorkshire, United Kingdom water supply network as part of Project NEPTUNE EP/E003192/1 ). A data analysissystem based on Kalman filtering and statistical approach has been developed. The system has been applied to the analysis of flow and pressure data. The system was proved for one dataset case and have shown the ability to detect anomalies in flow and pres sure patterns, by correlating with other information. It will be shown that the Kalman/statistical approach is a promising approach at detecting subtle changes and higher frequency features, it has the potential to identify precursor features and smaller l eaks and hence could be useful for monitoring the development of leaks, prior to a large volume burst event.

ANALISA POTENSI MINYAK DAN GAS BUMI DENGAN ATRIBUT SEISMIK PADA BATUAN KARBONAT LAPANGAN *ZEFARA* CEKUNGAN SUMATRA SELATAN

KURVATEK ◽  
2017 ◽  
Vol 1 (2) ◽  
pp. 21-31
Author(s):  
Fatimah Miharno
Keyword(s):  
Instantaneous Frequency ◽  
Carbonate Reservoir ◽  
Control Analysis ◽  
High Porosity ◽  
Hydrocarbon Accumulation ◽  
Seismic Attribute ◽  
Data Set ◽  
Log Data ◽  
Low Amplitude ◽  
Rms Amplitude

ABSTRACT*Zefara* Field formation Baturaja on South Sumatra Basin is a reservoir carbonate and prospective gas. Data used in this research were 3D seismik data, well logs, and geological information. According to geological report known that hidrocarbon traps in research area were limestone lithological layer as stratigraphical trap and faulted anticline as structural trap. The study restricted in effort to make a hydrocarbon accumulation and a potential carbonate reservoir area maps with seismic attribute. All of the data used in this study are 3D seismic data set, well-log data and check-shot data. The result of the analysis are compared to the result derived from log data calculation as a control analysis. Hydrocarbon prospect area generated from seismic attribute and are divided into three compartments. The seismic attribute analysis using RMS amplitude method and instantaneous frequency is very effective to determine hydrocarbon accumulation in *Zefara* field, because low amplitude from Baturaja reservoir. Low amplitude hints low AI, determined high porosity and high hydrocarbon contact (HC).  Keyword: Baturaja Formation, RMS amplitude seismic attribute, instantaneous frequency seismic attribute

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