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A new method to detect words that are likely to be confused by speech recognition systems is presented in this letter. A new dissimilarity measure between two words is calculated in two steps. First, the phonetic transcriptions of the words are aligned using only phonetic information. Two kinds of alignments are used: either with or without insertions and(More)
Voice imitation is one of the potential threats to security systems that use automatic speaker recognition. Since prosodic features have been considered for state-of-the-art recognition systems in recent years, the question arises as to how vulnerable these features are to voice mimicking. In this study, two experiments are conducted for twelve individual(More)
BACKGROUND The single-blind, placebo controlled oral challenge (SBPCOC) is the definitive way to diagnosis nonsteroidal anti-inflammatory drug (NSAID)-induced reactions. OBJECTIVE To evaluate 223 NSAID-sensitive patients by means of SBPCOC, and to describe the main clinical patterns found. METHODS A prospective study was carried out, including 2 patient(More)
In this paper, we address the modality integration issue on the example of a smart room environment aiming at enabling person identification by combining speech and 2D face images. First we introduce the monomodal audio and video identification techniques and then we present the use of combined input speech and face images for person identification. The(More)
A new method to predict if two words are likely to be confused by an Automatic Speech Recognition (ASR) system is presented in this paper. A new inter-word dissimilarity measure based on Dynamic Time Warping (DTW) is used to classify the word pairs as confusable or not confusable. Firstly, the phonetic transcriptions of the two words to compare are aligned(More)
BACKGROUND Sinapis alba (white mustard) is a entomophilic species included in the Brassicaceae family. To date it has not been related to allergic sensitization or clinical respiratory disease. METHODS Twelve olive orchard workers had a history of rhinitis and/or bronchial asthma that occurred during control weed management and/or harvest, from January to(More)
Jacobian Adaptation (JA) has been successfully used in Automatic Speech Recognition (ASR) systems to adapt the acoustic models from the training to the testing noise conditions. In this work we present an improvement of JA for speaker verification, where a specific training noise reference is estimated for each speaker model. The new proposal, which will be(More)
Jacobian Adaptation (JA) of the acoustic models is a fast adaptation technique that has been used in Automatic Speech Recognition (ASR) systems to adapt the models from the training to the testing noise conditions. This technique has been tested in previous works with both Mel-Frequency Cepstrum Coefficients (MFCC) and Frequency Filtering (FF) parameters(More)
In this work we investigate new inter-phone and inter-word distances and we apply them to predict if two words of the lexicon of an Automatic Speech Recognition (ASR) system are likely to be confused. The inter-word distance is calculated from an alignment between the phonetic transcriptions of the words by adding the distances between the aligned phones.(More)