Query-by-Example Spoken Term Detection ALBAYZIN 2012 evaluation: overview, systems, results, and discussion

Query-by-Example Spoken Term Detection (QbE STD) aims at retrieving data from a speech data repository given an acoustic query containing the term of interest as input. Nowadays, it has been receiving much interest due to the high volume of information stored in audio or audiovisual format. QbE STD differs from automatic speech recognition (ASR) and keyword spotting (KWS)/spoken term detection (STD) since ASR is interested in all the terms/words that appear in the speech signal and KWS/STD relies on a textual transcription of the search term to retrieve the speech data. This paper presents the systems submitted to the ALBAYZIN 2012 QbE STD evaluation held as a part of ALBAYZIN 2012 evaluation campaign within the context of the IberSPEECH 2012 Conference(a). The evaluation consists of retrieving the speech files that contain the input queries, indicating their start and end timestamps within the appropriate speech file. Evaluation is conducted on a Spanish spontaneous speech database containing a set of talks from MAVIR workshops(b), which amount at about 7 h of speech in total. We present the database metric systems submitted along with all results and some discussion. Four different research groups took part in the evaluation. Evaluation results show the difficulty of this task and the limited performance indicates there is still a lot of room for improvement. The best result is achieved by a dynamic time warping-based search over Gaussian posteriorgrams/posterior phoneme probabilities. This paper also compares the systems aiming at establishing the best technique dealing with that difficult task and looking for defining promising directions for this relatively novel task.

Pharmacogenetics of MicroRNAs and MicroRNAs Biogenesis Machinery in Pediatric Acute Lymphoblastic Leukemia

Despite the clinical success of acute lymphoblastic leukemia (ALL) therapy, toxicity is frequent. Therefore, it would be useful to identify predictors of adverse effects. In the last years, several studies have investigated the relationship between genetic variation and treatment-related toxicity. However, most of these studies are focused in coding regions. Nowadays, it is known that regions that do not codify proteins, such as microRNAs (miRNAs), may have an important regulatory function. MiRNAs can regulate the expression of genes affecting drug response. In fact, the expression of some of those miRNAs has been associated with drug response. Genetic variations affecting miRNAs can modify their function, which may lead to drug sensitivity. The aim of this study was to detect new toxicity markers in pediatric B-ALL, studying miRNA-related polymorphisms, which can affect miRNA levels and function. We analyzed 118 SNPs in pre-miRNAs and miRNA processing genes in association with toxicity in 152 pediatric B-ALL patients all treated with the same protocol (LAL/SHOP). Among the results found, we detected for the first time an association between rs639174 in DROSHA and vomits that remained statistically significant after FDR correction. DROSHA had been associated with alterations in miRNAs expression, which could affect genes involved in drug transport. This suggests that miRNA-related SNPs could be a useful tool for toxicity prediction in pediatric B-ALL.