Publications

The information in its audio form represents a large mass of data. The manipulation of this mass requires an automation. The goal of our work is to detect the reuse of audio information in other sequences, like the reuse of a press dispatch. People find difficulties in the use of information in his audio format and especially in the search for an audio sequence in different places. In order to help people, we focus our work on the problem of finding an audio subsequence in a distributed audio database. The search will be in voice mode where the user dictates a text into microphone. The goal is to receive the text dictated by user from the microphone and compare it with all sequences of the database and then returns the closest sequence to the dictated one. This goal requires a great work which will be proposed as a doctoral subject. In this paper we propose to acquire the query by playing a sequence of the database and to capture it by microphone. This paper presents a new system that identifies an audio subsequence using basic audio descriptors. Each audio document of corpus is pre-processed before the extraction of a set of basic audio descriptors, which characterize the temporal and the spectral information. Therefore, an audio signal is represented by a sequence of characteristics called in this paper "audio fingerprint". The search process is based on a new concept called “interference wave”. This wave is generated from the content of audio signals, and used to calculate the similarity rate between two audio signals.

In these recent years Wireless Sensor Networks (WSN) has been widely used in many types of applications such as environment monitoring or asset tracking. In these applications, each sensor node may collect different types of data with different levels of importance. Each type of traffic requires a different treatment from the network to meet the objective of QoS (Quality of Service). We argue that the sensor networks should be willing to spend more resources in disseminating packets that carry more important information. In this paper we propose a new protocol with differentiated services for WSNs called Diff-HEEP. The proposed protocol is an enhancement of HEEP protocol that can provide requested quality of service for high priority real time classes and distinguish high priority real time traffic from the low priority non-real time traffic, and input traffic streams are then served based on their priorities.