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Program Implementation of an Algorithm for Recognition of Speech Signals in the Labview Graphics Programming Environment
TLDR
Results from tests of the implementation and an analysis of the precision of recognition of sounds, words, and word combinations with the use of the newly developed base of speech signals are presented.
Methods to Improve the Efficiency of Recognition of Speech Signals in Voice Control Systems
An improved speech recognition algorithm has been developed with additional signal processing units to increase the number of comparative data parameters and to reduce the natural and spectral
An Algorithm for Measurement of the Pitch Frequency of Speech Signals Based on Complementary Ensemble Decomposition Into Empirical Modes
TLDR
A new algorithm based on complementary ensemble empirical mode decomposition is developed and the results confirm the robustness of the algorithm in the presence of frequency modulation of the pitch of speech signals.
Adaptive Signal Processing Method for Speech Organ Diagnostics
TLDR
The mean energy value of the Hilbert spectrum of a speech signal obtained by the complementary ensemble empirical mode decomposition and the Hilbert–Huang transform is shown in different ranges depending on the choice of phrases formed by separate active organs of the speech apparatus.
The emperical mode decomposition for ECG signal preprocessing
TLDR
It is proposed to use the Hilbert-Huang transform, which will allow ensuring the reduction of the level of the most characteristic interference with minimal distortion of the useful component of the ECG signal.
Improved CEEMDAN Based Speech Signal Analysis Algorithm for Mental Disorders Diagnostic System: Pitch Frequency Detection and Measurement
TLDR
The developed algorithm for pitch frequency measurement provides an accuracy increase in determination of borderline mental disorders: for the error of the first kind, on the average, it is more accurate by 10.7%, and for the second type error by 4.7%.
An Adaptive Speech Segmentation Algorithm to Determine Temporal Patterns of Human Psycho-Emotional States
TLDR
It was concluded that the developed adaptive algorithm more accurately determines the boundaries of informative areas, due to the advantages of the energy analysis of the modes obtained by the method of adaptive decomposition.
Noise-Robust Algorithm for "Speech/Pause" Segmentation in Diagnostic Systems of Psychogenic States
TLDR
A comparison of researches' results suggests that the developed 'speech/pause' segmentation algorithm is recommended for practical application in the diagnostic systems of psychogenic states, operating under free physical activity of a patient.
A Novel Approach to Speech Signal Segmentation Based on Empirical Mode Decomposition to Assess Human Psycho-Emotional State
TLDR
It was concluded that the method based on the developed technology determines the boundaries of informative sections more accurately, and it can be successfully tested at the preprocessing stages in the systems for detection and assessment of human psycho-emotional disorder.
Measurement of speech signal patterns under borderline mental disorders
TLDR
The developed algorithm for pitch frequency measurement provides an accuracy increase in determination of borderline mental disorders: for the error of the first kind, on the average, it is more accurate by 10.7%, and for the second type error by 4.7%.
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