scholarly journals Secure Speech Transmission Using Chaos Encryption System for AMR-WB Codec

2017 ◽  
Vol 5 (1) ◽  
pp. 118-126
Author(s):  
Messaouda Boumaraf ◽  
Fatiha Merazka
Keyword(s):  
Chaos Encryption ◽  
Speech Transmission

scholarly journals Acoustic Reconstruction of Eszterháza Opera House Following New Archival Research

2020 ◽  
Vol 10 (24) ◽  
pp. 8817
Author(s):  
Lamberto Tronchin ◽  
Francesca Merli ◽  
Marco Dolci
Keyword(s):  
3D Model ◽  
18Th Century ◽  
Second World War ◽  
World War ◽  
National Library ◽  
Acoustic Parameters ◽  
Speech Transmission ◽  
The Will ◽  
Opera House ◽  
Second World

The Eszterháza Opera House was a theatre built by the will of the Hungarian Prince Nikolaus Esterházy in the second half of the 18th century that had to compete in greatness and grandeur against Austrian Empire. The composer that inextricably linked his name to this theatre was Haydn that served the prince and composed pieces for him for many years. The Opera House disappeared from the palace complex maps around 1865 and was destroyed permanently during the Second World War. This study aims to reconstruct the original shape and materials of the theatre, thanks to the documents founded by researchers in the library of the Esterházy family at Forchtenstein, the Hungarian National Library, and analyze its acoustic behavior. With the 3D model of the theatre, acoustic simulations were performed using the architectural acoustic software Ramsete to understand its acoustical characteristics and if the architecture of the Eszterháza Opera House could favor the Prince’s listening. The obtained results show that the union between the large volume of the theatre and the reflective materials makes the Opera House a reverberant space. The acoustic parameters are considered acoustically favorable both for the music and for the speech transmission too. Moreover, the results confirm that the geometry and the shape of the Eszterháza Opera House favored the Prince’s view and listening, amplifying onstage voices and focusing the sound into his box.

scholarly journals High-Capacity Reversible Data Hiding in Encrypted Images by Information Preprocessing

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xi-Yan Li ◽  
Xia-Bing Zhou ◽  
Qing-Lei Zhou ◽  
Shi-Jing Han ◽  
Zheng Liu
Keyword(s):  
Data Hiding ◽  
Reversible Data Hiding ◽  
High Capacity ◽  
Main Idea ◽  
Original Image ◽  
Chaos Encryption ◽  
Secret Information ◽  
Encrypted Image ◽  
Encrypted Images ◽  
Scanned Documents

With the development of cloud computing, high-capacity reversible data hiding in an encrypted image (RDHEI) has attracted increasing attention. The main idea of RDHEI is that an image owner encrypts a cover image, and then a data hider embeds secret information in the encrypted image. With the information hiding key, a receiver can extract the embedded data from the hidden image; with the encryption key, the receiver reconstructs the original image. In this paper, we can embed data in the form of random bits or scanned documents. The proposed method takes full advantage of the spatial correlation in the original images to vacate the room for embedding information before image encryption. By jointly using Sudoku and Arnold chaos encryption, the encrypted images retain the vacated room. Before the data hiding phase, the secret information is preprocessed by a halftone, quadtree, and S-BOX transformation. The experimental results prove that the proposed method not only realizes high-capacity reversible data hiding in encrypted images but also reconstructs the original image completely.

Speaker Verification by Human Listeners over Several Speech Transmission Systems

1978 ◽  
Vol 57 (8) ◽  
pp. 2887-2900 ◽  
Author(s):  
C. A. McGonegal ◽  
L. R. Rabiner ◽  
B. J. McDermott
Keyword(s):  
Speaker Verification ◽  
Transmission Systems ◽  
Speech Transmission

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.

Binaural speech-to-noise loudness ratio at the speech reception threshold in vehicles

2021 ◽  
Vol 69 (2) ◽  
pp. 173-179
Author(s):  
Nilolina Samardzic ◽  
Brian C.J. Moore
Keyword(s):  
Speech Intelligibility ◽  
New Method ◽  
Traditional Methods ◽  
Speech Reception ◽  
Typical Error ◽  
Transmission Index ◽  
Speech Transmission ◽  
Articulation Index ◽  
Speech Intelligibility Index ◽  
Binaural Listening

Traditional methods for predicting the intelligibility of speech in the presence of noise inside a vehicle, such as the Articulation Index (AI), the Speech Intelligibility Index (SII), and the Speech Transmission Index (STI), are not accurate, probably because they do not take binaural listening into account; the signals reaching the two ears can differ markedly depending on the positions of the talker and listener. We propose a new method for predicting the intelligibility of speech in a vehicle, based on the ratio of the binaural loudness of the speech to the binaural loudness of the noise, each calculated using the method specified in ISO 532-2 (2017). The method was found to give accurate predictions of the speech reception threshold (SRT) measured under a variety of conditions and for different positions of the talker and listener in a car. The typical error in the predicted SRT was 1.3 dB, which is markedly smaller than estimated using the SII and STI (2.0 dB and 2.1 dB, respectively).

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