984 resultados para speech recognition
Resumo:
Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although these techniques are extremely powerful and well developed, both have important limitations. By fusing these techniques together to form Bayes-Markov chains, the advantages of both techniques can be preserved, while reducing their limitations. The Bayes-Markov technique forms the basis of a common, flexible framework for supplementing Markov chains with additional features. This results in improved user output, and aids in the rapid development of flexible and efficient behaviour recognition systems.
Resumo:
Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.
Resumo:
The experiment asks whether constancy in hearing precedes or follows grouping. Listeners heard speech-like sounds comprising 8 auditory-filter shaped noise-bands that had temporal envelopes corresponding to those arising in these filters when a speech message is played. The „context‟ words in the message were “next you‟ll get _to click on”, into which a “sir” or “stir” test word was inserted. These test words were from an 11-step continuum that was formed by amplitude modulation. Listeners identified the test words appropriately and quite consistently, even though they had the „robotic‟ quality typical of this type of 8-band speech. The speech-like effects of these sounds appears to be a consequence of auditory grouping. Constancy was assessed by comparing the influence of room reflections on the test word across conditions where the context had either the same level of reflections, or where it had a much lower level. Constancy effects were obtained with these 8-band sounds, but only in „matched‟ conditions, where the room reflections were in the same bands in both the context and the test word. This was not the case in a comparison „mismatched‟ condition, and here, no constancy effects were found. It would appear that this type of constancy in hearing precedes the across-channel grouping whose effects are so apparent in these sounds. This result is discussed in terms of the ubiquity of grouping across different levels of representation.
Resumo:
We study the complex formation of a peptide betaAbetaAKLVFF, previously developed by our group, with Abeta(1–42) in aqueous solution. Circular dichroism spectroscopy is used to probe the interactions between betaAbetaAKLVFF and Abeta(1–42), and to study the secondary structure of the species in solution. Thioflavin T fluorescence spectroscopy shows that the population of fibers is higher in betaAbetaAKLVFF/Abeta(1–42) mixtures compared to pure Abeta(1–42) solutions. TEM and cryo-TEM demonstrate that co-incubation of betaAbetaAKLVFF with Abeta(1–42) causes the formation of extended dense networks of branched fibrils, very different from the straight fibrils observed for Abeta(1–42) alone. Neurotoxicity assays show that although betaAbetaAKLVFF alters the fibrillization of Abeta(1–42), it does not decrease the neurotoxicity, which suggests that toxic oligomeric Abeta(1–42) species are still present in the betaAbetaAKLVFF/Abeta(1–42) mixtures. Our results show that our designed peptide binds to Abeta(1–42) and changes the amyloid fibril morphology. This is shown to not necessarily translate into reduced toxicity.
Resumo:
Sequence-specific binding is demonstrated between pyrene-based tweezer molecules and soluble, high molar mass copolyimides. The binding involves complementary pi - pi stacking interactions, polymer chain-folding, and hydrogen bonding and is extremely sensitive to the steric environment around the pyromellitimide binding-site. A detailed picture of the intermolecular interactions involved has been obtained through single-crystal X-ray studies of tweezer complexes with model diimides. Ring-current magnetic shielding of polyimide protons by the pyrene '' arms '' of the tweezer molecule induces large complexation shifts of the corresponding H-1 NMR resonances, enabling specific triplet sequences to be identified by their complexation shifts. Extended comonomer sequences (triplets of triplets in which the monomer residues differ only by the presence or absence of a methyl group) can be '' read '' by a mechanism which involves multiple binding of tweezer molecules to adjacent diimide residues within the copolymer chain. The adjacent-binding model for sequence recognition has been validated by two conceptually different sets of tweezer binding experiments. One approach compares sequence-recognition events for copolyimides having either restricted or unrestricted triple-triplet sequences, and the other makes use of copolymers containing both strongly binding and completely nonbinding diimide residues. In all cases the nature and relative proportions of triple-triplet sequences predicted by the adjacent-binding model are fully consistent with the observed H-1 NMR data.
Resumo:
In order to explore the impact of a degraded semantic system on the structure of language production, we analysed transcripts from autobiographical memory interviews to identify naturally-occurring speech errors by eight patients with semantic dementia (SD) and eight age-matched normal speakers. Relative to controls, patients were significantly more likely to (a) substitute and omit open class words, (b) substitute (but not omit) closed class words, (c) substitute incorrect complex morphological forms and (d) produce semantically and/or syntactically anomalous sentences. Phonological errors were scarce in both groups. The study confirms previous evidence of SD patients’ problems with open class content words which are replaced by higher frequency, less specific terms. It presents the first evidence that SD patients have problems with closed class items and make syntactic as well as semantic speech errors, although these grammatical abnormalities are mostly subtle rather than gross. The results can be explained by the semantic deficit which disrupts the representation of a pre-verbal message, lexical retrieval and the early stages of grammatical encoding.
Resumo:
Virulence in Staphylococcus aureus is regulated via agr-dependent quorum sensing in which an autoinducing peptide (AIP) activates AgrC, a histidine protein kinase. AIPs are usually thiolactones containing seven to nine amino acid residues in which the thiol of the central cysteine is linked to the alpha-carboxyl of the C-terminal amino acid residue. The staphylococcal agr locus has diverged such that the AIPs of the four different S. aureus agr groups self-activate but cross-inhibit. Consequently, although the agr system is conserved among the staphylococci, it has undergone significant evolutionary divergence whereby to retain functionality, any changes in the AIP-encoding gene (agrD) that modifies AIP structure must be accompanied by corresponding changes in the AgrC receptor. Since AIP-1 and AIP-4 only differ by a single amino acid, we compared the transmembrane topology of AgrC1 and AgrC4 to identify amino acid residues involved in AIP recognition. As only two of the three predicted extracellular loops exhibited amino acid differences, site-specific mutagenesis was used to exchange the key AgrC1 and AgrC4 amino acid residues in each loop either singly or in combination. A novel lux-based agrP3 reporter gene fusion was constructed to evaluate the response of the mutated AgrC receptors. The data obtained revealed that while differential recognition of AIP-1 and AIP-4 depends primarily on three amino acid residues in loop 2, loop 1 is essential for receptor activation by the cognate AIP. Furthermore, a single mutation in the AgrC1 loop 2 resulted in conversion of (Ala5)AIP-1 from a potent antagonist to an activator, essentially resulting in the forced evolution of a new AIP group. Taken together, our data indicate that loop 2 constitutes the predicted hydrophobic pocket that binds the AIP thiolactone ring while the exocyclic amino acid tail interacts with loop 1 to facilitate receptor activation.
Resumo:
This paper reports the pitch range and vowel duration data from a group of children with Williams syndrome (WS) in comparison with a group of typically developing children matched for chronological age (CA) and a group matched for receptive language abilities (LA). It is found that the speech of the WS group has a greater pitch range and that vowels tend to be longer in duration than in the speech of the typically developing children. These findings are in line with the impressionistic results reported by Reilly, Klima and Bellugi [17].
Resumo:
A new class of shape features for region classification and high-level recognition is introduced. The novel Randomised Region Ray (RRR) features can be used to train binary decision trees for object category classification using an abstract representation of the scene. In particular we address the problem of human detection using an over segmented input image. We therefore do not rely on pixel values for training, instead we design and train specialised classifiers on the sparse set of semantic regions which compose the image. Thanks to the abstract nature of the input, the trained classifier has the potential to be fast and applicable to extreme imagery conditions. We demonstrate and evaluate its performance in people detection using a pedestrian dataset.