Sentence boundary detection for transcribed Tunisian Arabic

International audienceWe study, in this paper, the problem of detecting the sentence boundary in tran-scribed spoken Tunisian Arabic. We compare and contrast three different methods for detecting sentence bounda-ries in transcribed speech. The first method uses a set of handmade contex-tual patterns for identifying the limit of sentences. The second method aims to classify transcriptions words into four classes according to their position in a sentence. Both methods are based only on lexical and some prosodic information such as silent and filled pauses. Finally, we develop two techniques for mixing the results of the two proposed methods. We show that sentence boundary detec-tion system can improve the accuracy of a POS tagger system developed for tag-ging transcribed Tunisian Arabic

Microsatellite Typing To Trace Aspergillus flavus Infections in a Hematology Unit ▿

Assessing the relatedness of strains isolated from patients and their environment is instrumental in documenting the source of preventable health care-associated life-threatening Aspergillus flavus human infection clusters. The present study aimed at identifying and selecting suitable microsatellite markers for A. flavus typing. This typing scheme was then applied to investigate the A. flavus epidemiology within a hematology unit in Sfax, Tunisia. Use of a combination of five markers made it possible to discern clusters of isolates and to substantiate the genetic diversity of A. flavus within clusters. Isolates from Tunisia and Marseille, France, displayed distinct haplotypes, indicating a highly significant geographical structuring of A. flavus. The typing of clinical and environmental A. flavus isolates in a hematology unit provided insights into its hospital epidemiology. From a heterogeneous genetic background, a cluster indicative of a clonal propagation episode within the unit could be identified. In two patients with invasive aspergillosis, the same genotype was found in clinical and environmental isolates, indicating hospital-acquired colonization and infection. In further studies, this novel microsatellite typing scheme might be instrumental in illuminating important epidemiological issues about A. flavus population genetics or epidemiology, including tracing the sources and routes of transmission

Morphological disambiguation of Tunisian dialect

International audienceIn this paper, we propose a method to disambiguate the output of a morphological analyzer of the Tunisian dialect. We test three machine-learning techniques that classify the morphological analysis of each word token into two classes: true and false. The class label is assigned to each analysis according to the context of the corresponding word in a sentence. In failure cases, we combine the results of the proposed techniques with a bigram classifier to choose only one analysis for a given word. We disam-biguate the result of the morphological analyzer of the Tunisian Dialect Al-Khalil-TUN (Zribi et al., 2013b). We use the Spoken Tunisian Arabic Corpus STAC (Zribi et al., 2015) to train and test our method. The evaluation shows that the proposed method has achieved an accuracy performance of 87.32%. Ó 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Critical description of TA linguistic resources

International audienceThis paper presents a critical description of natural language processing for Tunisian Arabic. Indeed, several linguistic resources were proposed for the three types of Tunisian Arabic (intellectualized dialect, spontaneous dialect and electronic dialect). We present different linguistic resources (corpora, lexicons and linguistic analysis tools). This study can be used as a quick reference for the scientific community working on natural language processing in general and more precisely those studying Tunisian Arabic

Microsatellite typing of Aspergillus flavus from clinical and environmental avian isolates

Aspergillosis is one of the most common causes of death in captive birds. Aspergillus fumigatus accounts for approximately 95 % of aspergillosis cases and Aspergillus flavus is the second most frequent organism associated with avian infections. In the present study, the fungi were grown from avian clinical samples (post-mortem lung material) and environmental samples (eggs, food and litter). Microsatellite markers were used to type seven clinical avian isolates and 22 environmental isolates of A. flavus. A. flavus was the only species (28 % prevalence) detected in the avian clinical isolates, whereas this species ranked third (19 %) after members of the genera Penicillium (39 %) and Cladosporium (21 %) in the environmental samples. Upon microsatellite analysis, five to eight distinct alleles were detected for each marker. The marker with the highest discriminatory power had eight alleles and a 0.852 D value. The combination of all six markers yielded a 0.991 D value with 25 distinct genotypes. One clinical avian isolate (lung biopsy) and one environmental isolate (egg) shared the same genotype. Microsatellite typing of A. flavus grown from avian and environmental samples displayed an excellent discriminatory power and 100 % reproducibility. This study showed a clustering of clinical and environmental isolates, which were clearly separated. Based upon these results, aspergillosis in birds may be induced by a great diversity of isolates