Speech Signal Analysis, Synthesis and Recognition Exercises Using Matlab

1997 ◽  
Vol 34 (2) ◽  
pp. 161-172 ◽  
Author(s):  
Robin W. King
Keyword(s):  
Signal Processing ◽  
Language Processing ◽  
Speech Signal ◽  
Signal Analysis ◽  
Engineering Students ◽  
Linear Prediction ◽  
Formant Synthesis ◽  
Elective Course ◽  
Speech Science ◽  
Speech And Language Processing

Three MATLAB exercises covering speech signal analysis and principles of linear prediction, formant synthesis and speech recognition are described. These exercises, which are assessed components in an elective course on speech and language processing, enable undergraduate electrical engineering students to explore fundamentally important concepts in speech science and signal processing.

scholarly journals Removal of Pink Noise from Corrupted Speech Signal using Kalman Filter

2020 ◽  
Vol 9 (4) ◽  
pp. 2034-2038
Keyword(s):  
Signal Processing ◽  
Kalman Filter ◽  
Speech Enhancement ◽  
Speech Signal ◽  
Linear Prediction ◽  
Audio Signal ◽  
Pink Noise ◽  
Linear Quadratic ◽  
Noise Component ◽  
Practical Applications

Speech enhancement has been a major challenge in the field of Signal processing. The process of filtering the noise component from the speech signal has achieved many milestones since the early 20th century. Beside many theories Linear prediction coding is one of the best methods for speech, audio signal processing which uses the algorithm of predicting the current estimates based on the past states of an LTI system. Linear prediction is usually used in Speech recognition, Speech enhancement. One of such Kalman filter was introduced and described in 1960 by Rudolf Kalman, which uses the concept of linear quadratic estimation. Kalman filtering is effectively being used in the practical applications like navigation of ships or aircraft, designing motion planning algorithms, in communication area. Kalman filters use the autoregression model of speech for the recursive equations of Kalman filter used in state space model of filter for state estimation. In this paper, we have used Kalman filter to eliminate the pink noise from the corrupted speech signal. Pink noise is very common in electronic devices and occurs in almost all devices. The Speech corrupted with pink noise has been obtained from SpEAR database. We have used MATLAB software for the simulation purpose. Finally, Spectrograms of signals are plotted for a better visual understanding of filtered results.

scholarly journals In Memoriam: Johan Liljencrants (1936–2012)

2012 ◽  
Vol 42 (2) ◽  
pp. 253-254
Author(s):  
Rolf Carlson ◽  
Björn Granström
Keyword(s):  
Signal Processing ◽  
Speech Signal ◽  
Speech Analysis ◽  
Speech Signal Processing ◽  
Speech Synthesizer ◽  
Speech Transmission ◽  
Analysis And Synthesis ◽  
In Memoriam ◽  
The 1960S

Johan Liljencrants was a KTH oldtimer. His interests focused early on speech analysis and synthesis where in the 1960s he took a leading part in the development of analysis hardware, the OVE III speech synthesizer, and the introduction of computers in the Speech Transmission Laboratory. Later work shifted toward general speech signal processing, for instance in his thesis on the use of a reflection line synthesizer. His interests expanded to modelling the glottal system, parametrically as in the Liljencrants–Fant (LF) model of glottal waveshapes, as well as physically including glottal aerodynamics and mechanics.

Sign in / Sign up

Export Citation Format

Share Document