Recognizing Voice Over IP: A Robust Front-End for Speech Recognition on the World Wide Web

The Internet Protocol (IP) environment poses two relevant sources of distortion to the speech recognition problem: lossy speech coding and packet loss. In this paper, we propose a new front-end for speech recognition over IP networks. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bit stream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant benefits. 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 due to the encoding-decoding process. Second, when packet loss occurs, our front-end becomes more effective since it is not constrained to the error handling mechanism of the codec. We have considered the ITU G.723.1 standard codec, which is one of the most preponderant coding algorithms in voice over IP (VoIP) and compared the proposed front-end with the conventional approach in two automatic speech recognition (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 packet loss rates. Furthermore, the improvement is higher as network conditions worsen.Publicad

VoIP Packet Delay Techniques: A Survey

The continuous development in the field of communication have paved the way for Voice over Internet Protocol (VoIP). VoIP is a group of hardware and software that facilitates people to utilize the Internet as the transmission medium for telephone calls by transmitting voice data in packets using IP instead of using conventional circuit transmissions of the Public Switched Telephone Network (PSTN). At present, VoIP is becoming an important tool for quick communication across the world. There are several Internet telephony applications existing at present. The major disadvantage in VoIP is that the packet delay. In VoIP, the terminology jitter is used to refer the type of packet delay where the delay has a huge setback in the quality of the voice conversation. Several packet delay techniques were proposed in recent years. Some of the important packet delay techniques are discussed in the literature. This survey would definitely help the researchers to carry out their research for providing better communication in VoIP without any delay

On Privacy of Encrypted Speech Communications

Silence suppression, an essential feature of speech communications over the Internet, saves bandwidth by disabling voice packet transmissions when silence is detected. However, silence suppression enables an adversary to recover talk patterns from packet timing. In this paper, we investigate privacy leakage through the silence suppression feature. More specifically, we propose a new class of traffic analysis attacks to encrypted speech communications with the goal of detecting speakers of encrypted speech communications. These attacks are based on packet timing information only and the attacks can detect speakers of speech communications made with different codecs. We evaluate the proposed attacks with extensive experiments over different type of networks including commercial anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speakers of encrypted speech communications with high accuracy based on traces of 15 minutes long on average

On Traffic Analysis Attacks to Encrypted VOIP Calls

The increasing popularity of VoIP telephony has brought a lot of attention and concern over security and privacy issues of VoIP communication. This thesis proposes a new class of traffic analysis attacks to encrypted VoIP calls. The goal of these attacks is to detect speaker or speech of encrypted VoIP calls. The proposed traffic analysis attacks exploit silent suppression, an essential feature of VoIP telephony. These attacks are based on application-level features so that the attacks can detect the same speech or the same speaker of different VoIP calls made with different VoIP codecs. We evaluate the proposed attacks by extensive experiments over different type of networks including commercialized anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speaker and speech of encrypted VoIP calls with a high detection rate which is a great improvement comparing with random guess. With the help of intersection attacks, the detection rate for speaker detection can be increased. In order to shield the detrimental effect of this proposed attacks, a countermeasure is proposed to mitigate the proposed traffic analysis attack

On Traffic Analysis Attacks to Encrypted VOIP Calls

The increasing popularity of VoIP telephony has brought a lot of attention and concern over security and privacy issues of VoIP communication. This thesis proposes a new class of traffic analysis attacks to encrypted VoIP calls. The goal of these attacks is to detect speaker or speech of encrypted VoIP calls. The proposed traffic analysis attacks exploit silent suppression, an essential feature of VoIP telephony. These attacks are based on application-level features so that the attacks can detect the same speech or the same speaker of different VoIP calls made with different VoIP codecs. We evaluate the proposed attacks by extensive experiments over different type of networks including commercialized anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speaker and speech of encrypted VoIP calls with a high detection rate which is a great improvement comparing with random guess. With the help of intersection attacks, the detection rate for speaker detection can be increased. In order to shield the detrimental effect of this proposed attacks, a countermeasure is proposed to mitigate the proposed traffic analysis attack

QoE Modelling, Measurement and Prediction: A Review

In mobile computing systems, users can access network services anywhere and anytime using mobile devices such as tablets and smart phones. These devices connect to the Internet via network or telecommunications operators. Users usually have some expectations about the services provided to them by different operators. Users' expectations along with additional factors such as cognitive and behavioural states, cost, and network quality of service (QoS) may determine their quality of experience (QoE). If users are not satisfied with their QoE, they may switch to different providers or may stop using a particular application or service. Thus, QoE measurement and prediction techniques may benefit users in availing personalized services from service providers. On the other hand, it can help service providers to achieve lower user-operator switchover. This paper presents a review of the state-the-art research in the area of QoE modelling, measurement and prediction. In particular, we investigate and discuss the strengths and shortcomings of existing techniques. Finally, we present future research directions for developing novel QoE measurement and prediction technique

Predicting Multimedia Traffic in Wireless Networks: A Performance Evaluation of Cognitive Techniques

Traffic engineering in networking is defined as the process that incorporates sophisticated methods in order to ensure optimization and high network performance. One of the most constructive tools employed by the traffic engineering concept is the traffic prediction. Having in mind the heterogeneous traffic patterns originated by various modern services and network platforms, the need of a robust, cognitive, and error-free prediction technique becomes even more pressing. This work focuses on the prediction concept as an autonomous, functional, and efficient process, where multiple cutting-edge methods are presented, modeled, and thoroughly assessed. To this purpose, real traffic traces have been captured, including multiple multimedia traffic flows, so as to comparatively assess widely used methods in terms of accuracy

Predicting Multimedia Traffic in Wireless Networks: A Performance Evaluation of Cognitive Techniques

Traffic engineering in networking is defined as the process that incorporates sophisticated methods in order to ensure optimization and high network performance. One of the most constructive tools employed by the traffic engineering concept is the traffic prediction. Having in mind the heterogeneous traffic patterns originated by various modern services and network platforms, the need of a robust, cognitive, and error-free prediction technique becomes even more pressing. This work focuses on the prediction concept as an autonomous, functional, and efficient process, where multiple cutting-edge methods are presented, modeled, and thoroughly assessed. To this purpose, real traffic traces have been captured, including multiple multimedia traffic flows, so as to comparatively assess widely used methods in terms of accuracy