Band-pass filtering of the time sequences of spectral parameters for robust wireless speech recognition

In this paper we address the problem of automatic speech recognition when wireless speech communication systems are involved. In this context, three main sources of distortion should be considered: acoustic environment, speech coding and transmission errors. Whilst the first one has already received a lot of attention, the last two deserve further investigation in our opinion. We have found out that band-pass filtering of the recognition features improves ASR performance when distortions due to these particular communication systems are present. Furthermore, we have evaluated two alternative configurations at different bit error rates (BER) typical of these channels: band-pass filtering the LP-MFCC parameters or a modification of the RASTA-PLP using a sharper low-pass section perform consistently better than LP-MFCC and RASTA-PLP, respectively.Publicad

Recognizing GSM Digital Speech

The Global System for Mobile (GSM) environment encompasses three main problems for automatic speech recognition (ASR) systems: noisy scenarios, source coding distortion, and transmission errors. The first one has already received much attention; however, source coding distortion and transmission errors must be explicitly addressed. In this paper, we propose an alternative front-end for speech recognition over GSM networks. This front-end is specially conceived to be effective against source coding distortion and transmission errors. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bitstream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant advantages. First, the recognition system is only affected by the quantization distortion of the spectral envelope. Thus, we are avoiding the influence of other sources of distortion as a result of the encoding-decoding process. Second, when transmission errors occur, our front-end becomes more effective since it is not affected by errors in bits allocated to the excitation signal. We have considered the half and the full-rate standard codecs and compared the proposed front-end with the conventional approach in two ASR tasks, namely, speaker-independent isolated digit recognition and speaker-independent continuous speech recognition. In general, our approach outperforms the conventional procedure, for a variety of simulated channel conditions. Furthermore, the disparity increases as the network conditions worsen

Distributed Speech Recognition

This article discusses possibilities of integrating speech technology into wireless technology, allowing voice input for wireless devices. Distributed speech recognition concept and activities related to its standardization are presented. First ETSI DSR MFCC based standard is described. Work on its extension to improve robustness resulting in new standard is also presented

Edge-centric multimodal authentication system using encrypted biometric templates

Data security, complete system control, and missed storage and computing opportunities in personal portable devices are some of the major limitations of the centralized cloud environment. Among these limitations, security is a prime concern due to potential unauthorized access to private data. Biometrics, in particular, is considered sensitive data, and its usage is subject to the privacy protection law. To address this issue, a multimodal authentication system using encrypted biometrics for the edge-centric cloud environment is proposed in this study. Personal portable devices are utilized for encrypting biometrics in the proposed system, which optimizes the use of resources and tackles another limitation of the cloud environment. Biometrics is encrypted using a new method. In the proposed system, the edges transmit the encrypted speech and face for processing in the cloud. The cloud then decrypts the biometrics and performs authentication to confirm the identity of an individual. The model for speech authentication is based on two types of features, namely, Mel-frequency cepstral coefficients and perceptual linear prediction coefficients. The model for face authentication is implemented by determining the eigenfaces. The final decision about the identity of a user is based on majority voting. Experimental results show that the new encryption method can reliably hide the identity of an individual and accurately decrypt the biometrics, which is vital for errorless authentication

A Cognitive Framework to Secure Smart Cities

The advancement in technology has transformed Cyber Physical Systems and their interface with IoT into a more sophisticated and challenging paradigm. As a result, vulnerabilities and potential attacks manifest themselves considerably more than before, forcing researchers to rethink the conventional strategies that are currently in place to secure such physical systems. This manuscript studies the complex interweaving of sensor networks and physical systems and suggests a foundational innovation in the field. In sharp contrast with the existing IDS and IPS solutions, in this paper, a preventive and proactive method is employed to stay ahead of attacks by constantly monitoring network data patterns and identifying threats that are imminent. Here, by capitalizing on the significant progress in processing power (e.g. petascale computing) and storage capacity of computer systems, we propose a deep learning approach to predict and identify various security breaches that are about to occur. The learning process takes place by collecting a large number of files of different types and running tests on them to classify them as benign or malicious. The prediction model obtained as such can then be used to identify attacks. Our project articulates a new framework for interactions between physical systems and sensor networks, where malicious packets are repeatedly learned over time while the system continually operates with respect to imperfect security mechanisms

Hospitality Information Systems: Intuitive, Object-Oriented, and Wireless Technology

Automated information system design and implementation is one of the fastest changing aspects of the hospitality industry. During the past several years nothing has increased the professionalism or improved the productivity within the industry more than the application of computer technology. Intuitive software applications, deemed the first step toward making computers more people-literate, object-oriented programming, intended to more accurately model reality, and wireless communications are expected to play a significant role in future technological advancement