291 resultados para Distúrbios da audição


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Spoken term detection (STD) is the task of looking up a spoken term in a large volume of speech segments. In order to provide fast search, speech segments are first indexed into an intermediate representation using speech recognition engines which provide multiple hypotheses for each speech segment. Approximate matching techniques are usually applied at the search stage to compensate the poor performance of automatic speech recognition engines during indexing. Recently, using visual information in addition to audio information has been shown to improve phone recognition performance, particularly in noisy environments. In this paper, we will make use of visual information in the form of lip movements of the speaker in indexing stage and will investigate its effect on STD performance. Particularly, we will investigate if gains in phone recognition accuracy will carry through the approximate matching stage to provide similar gains in the final audio-visual STD system over a traditional audio only approach. We will also investigate the effect of using visual information on STD performance in different noise environments.

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Bioacoustic monitoring has become a significant research topic for species diversity conservation. Due to the development of sensing techniques, acoustic sensors are widely deployed in the field to record animal sounds over a large spatial and temporal scale. With large volumes of collected audio data, it is essential to develop semi-automatic or automatic techniques to analyse the data. This can help ecologists make decisions on how to protect and promote the species diversity. This paper presents generic features to characterize a range of bird species for vocalisation retrieval. In the implementation, audio recordings are first converted to spectrograms using short-time Fourier transform, then a ridge detection method is applied to the spectrogram for detecting points of interest. Based on the detected points, a new region representation are explored for describing various bird vocalisations and a local descriptor including temporal entropy, frequency bin entropy and histogram of counts of four ridge directions is calculated for each sub-region. To speed up the retrieval process, indexing is carried out and the retrieved results are ranked according to similarity scores. The experiment results show that our proposed feature set can achieve 0.71 in term of retrieval success rate which outperforms spectral ridge features alone (0.55) and Mel frequency cepstral coefficients (0.36).

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Acoustic recordings play an increasingly important role in monitoring terrestrial environments. However, due to rapid advances in technology, ecologists are accumulating more audio than they can listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings by calculating acoustic indices. These are statistics which describe the temporal-spectral distribution of acoustic energy and reflect content of ecological interest. We combine spectral indices to produce false-color spectrogram images. These not only reveal acoustic content but also facilitate navigation. An additional analytic challenge is to find appropriate descriptors to summarize the content of 24-hour recordings, so that it becomes possible to monitor long-term changes in the acoustic environment at a single location and to compare the acoustic environments of different locations. We describe a 24-hour ‘acoustic-fingerprint’ which shows some preliminary promise.

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Unified communications as a service (UCaaS) can be regarded as a cost-effective model for on-demand delivery of unified communications services in the cloud. However, addressing security concerns has been seen as the biggest challenge to the adoption of IT services in the cloud. This study set up a cloud system via VMware suite to emulate hosting unified communications (UC), the integration of two or more real time communication systems, services in the cloud in a laboratory environment. An Internet Protocol Security (IPSec) gateway was also set up to support network-level security for UCaaS against possible security exposures. This study was aimed at analysis of an implementation of UCaaS over IPSec and evaluation of the latency of encrypted UC traffic while protecting that traffic. Our test results show no latency while IPSec is implemented with a G.711 audio codec. However, the performance of the G.722 audio codec with an IPSec implementation affects the overall performance of the UC server. These results give technical advice and guidance to those involved in security controls in UC security on premises as well as in the cloud.

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Engaging middle-school students in science continues to be a challenge in Australian schools. One initiative that has been tried in the senior years but is a more recent development in the middle years is the context-based approach. In this ethnographic study, we researched the teaching and learning transactions that occurred in one 9th grade science class studying a context-based Environmental Science unit that included visits to the local creek for 11 weeks. Data were derived from field notes, audio and video recorded conversations, interviews, student journals and classroom documents with a particular focus on two selected groups of students. This paper presents two assertions that highlight pedagogical approaches that contributed to learning. Firstly, spontaneous teaching episodes created opportunities for in-the-moment questioning by the teacher that led to students’ awareness of environmental issues and the scientific method; secondly, group work using flip cameras afforded opportunities for students to connect the science concepts with the context. Furthermore, students reported positively about the unit and expressed their appreciation for the opportunity to visit the creek frequently. This findings from this study should encourage teachers to take students into the real-world field for valuable teaching and learning experiences that are not available in the formal classroom.

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These are turbulent times for audio- visual production companies. Radical changes, both inside and outside the organizations, reach across national markets and different genres. For instance, production methods are changing; the demand from audiences and advertisers is changing; power relations between the actors involved in the value chain are changing; and increasing concentration makes the market even more competitive for small independent players. From a perspective of the structure–conduct– performance paradigm (Ramstad, 1997) it is reasonable to expect that these changes on a structural level of the industry will cause the production companies to adapt their strategic behaviour. The current challenges for media companies are a combination of rising complexity and uncertainty in the market (Picard, 2004). The increasing complexity can for instance be observed in the growing number of market segments and in the continuing trend towards cross- media strategies where media companies operate in multiple markets and on multiple platforms...

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Avian species richness surveys, which measure the total number of unique avian species, can be conducted via remote acoustic sensors. An immense quantity of data can be collected, which, although rich in useful information, places a great workload on the scientists who manually inspect the audio. To deal with this big data problem, we calculated acoustic indices from audio data at a one-minute resolution and used them to classify one-minute recordings into five classes. By filtering out the non-avian minutes, we can reduce the amount of data by about 50% and improve the efficiency of determining avian species richness. The experimental results show that, given 60 one-minute samples, our approach enables to direct ecologists to find about 10% more avian species.

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Frog species have been declining worldwide at unprecedented rates in the past decades. There are many reasons for this decline including pollution, habitat loss, and invasive species [1]. To preserve, protect, and restore frog biodiversity, it is important to monitor and assess frog species. In this paper, a novel method using image processing techniques for analyzing Australian frog vocalisations is proposed. An FFT is applied to audio data to produce a spectrogram. Then, acoustic events are detected and isolated into corresponding segments through image processing techniques applied to the spectrogram. For each segment, spectral peak tracks are extracted with selected seeds and a region growing technique is utilised to obtain the contour of each frog vocalisation. Based on spectral peak tracks and the contour of each frog vocalisation, six feature sets are extracted. Principal component analysis reduces each feature set down to six principal components which are tested for classification performance with a k-nearest neighbor classifier. This experiment tests the proposed method of classification on fourteen frog species which are geographically well distributed throughout Queensland, Australia. The experimental results show that the best average classification accuracy for the fourteen frog species can be up to 87%.

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Acoustic classification of anurans (frogs) has received increasing attention for its promising application in biological and environment studies. In this study, a novel feature extraction method for frog call classification is presented based on the analysis of spectrograms. The frog calls are first automatically segmented into syllables. Then, spectral peak tracks are extracted to separate desired signal (frog calls) from background noise. The spectral peak tracks are used to extract various syllable features, including: syllable duration, dominant frequency, oscillation rate, frequency modulation, and energy modulation. Finally, a k-nearest neighbor classifier is used for classifying frog calls based on the results of principal component analysis. The experiment results show that syllable features can achieve an average classification accuracy of 90.5% which outperforms Mel-frequency cepstral coefficients features (79.0%).

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Frogs have received increasing attention due to their effectiveness for indicating the environment change. Therefore, it is important to monitor and assess frogs. With the development of sensor techniques, large volumes of audio data (including frog calls) have been collected and need to be analysed. After transforming the audio data into its spectrogram representation using short-time Fourier transform, the visual inspection of this representation motivates us to use image processing techniques for analysing audio data. Applying acoustic event detection (AED) method to spectrograms, acoustic events are firstly detected from which ridges are extracted. Three feature sets, Mel-frequency cepstral coefficients (MFCCs), AED feature set and ridge feature set, are then used for frog call classification with a support vector machine classifier. Fifteen frog species widely spread in Queensland, Australia, are selected to evaluate the proposed method. The experimental results show that ridge feature set can achieve an average classification accuracy of 74.73% which outperforms the MFCCs (38.99%) and AED feature set (67.78%).

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This research has made contributions to the area of spoken term detection (STD), defined as the process of finding all occurrences of a specified search term in a large collection of speech segments. The use of visual information in the form of lip movements of the speaker in addition to audio and the use of topic of the speech segments, and the expected frequency of words in the target speech domain, are proposed. By using these complementary information, improvement in the performance of STD has been achieved which enables efficient search of key words in large collection of multimedia documents.

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Bioacoustic data can be used for monitoring animal species diversity. The deployment of acoustic sensors enables acoustic monitoring at large temporal and spatial scales. We describe a content-based birdcall retrieval algorithm for the exploration of large data bases of acoustic recordings. In the algorithm, an event-based searching scheme and compact features are developed. In detail, ridge events are detected from audio files using event detection on spectral ridges. Then event alignment is used to search through audio files to locate candidate instances. A similarity measure is then applied to dimension-reduced spectral ridge feature vectors. The event-based searching method processes a smaller list of instances for faster retrieval. The experimental results demonstrate that our features achieve better success rate than existing methods and the feature dimension is greatly reduced.

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Driving can be a lonely activity. While there has been a lot of research and technical inventions concerning car-to-car communication and passenger entertainment, there is still little work concerning connecting drivers. Whereas tourism is very much a social activity, drive tourists have few options to communicate with fellow travellers. The proposed project is placed at the intersection of tourism and driving and aims to enhance the trip experience during driving through social interaction. This thesis explores how a mobile application that allows instant messaging between travellers sharing similar context can add to road trip experiences. To inform the design of such an application, the project adopted the principle of the user-centred design process. User needs were assessed by running an ideation workshop and a field trip. Findings of both studies have shown that tourists have different preferences and diverse attitudes towards contacting new people. Yet all participants stressed the value of social recommendations. Based on those results and a later expert review, three prototype versions of the system were created. A prototyping session with potential end users highlighted the most important features including the possibility to view user profiles, choose between text and audio input and receive up-to-date information. An implemented version of the prototype was evaluated in an exploratory study to identify usability related problems in an actual use case scenario as well as to find implementation bugs. The outcomes of this research are relevant for the design of future mobile tourist guides that leverage from benefits of social recommendations.

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Purpose Peer-review programmes in radiation oncology are used to facilitate the process and evaluation of clinical decision-making. However, web-based peer-review methods are still uncommon. This study analysed an inter-centre, web-based peer-review case conference as a method of facilitating the decision-making process in radiation oncology. Methodology A benchmark form was designed based on the American Society for Radiation Oncology targets for radiation oncology peer review. This was used for evaluating the contents of the peer-review case presentations on 40 cases, selected from three participating radiation oncology centres. A scoring system was used for comparison of data, and a survey was conducted to analyse the experiences of radiation oncology professionals who attended the web-based peer-review meetings in order to identify priorities for improvement. Results The mean scores for the evaluations were 82·7, 84·5, 86·3 and 87·3% for cervical, prostate, breast and head and neck presentations, respectively. The survey showed that radiation oncology professionals were confident about the role of web-based peer-reviews in facilitating sharing of good practice, stimulating professionalism and promoting professional growth. The participants were satisfied with the quality of the audio and visual aspects of the web-based meeting. Conclusion The results of this study suggest that simple inter-centre web-based peer-review case conferences are a feasible technique for peer review in radiation oncology. Limitations such as data security and confidentiality can be overcome by the use of appropriate structure and technology. To drive the issues of quality and safety a step further, small radiotherapy departments may need to consider web-based peer-review case conference as part of their routine quality assurance practices.

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Objective To investigate the perspectives of general practitioners (GPs) on the practice of soliciting additional concerns (ACs) and the acceptability and utility of two brief interventions (prompts) designed to aid the solicitation. Methods Eighteen GPs participating in a feasibility randomised controlled trial were interviewed. Interviews were semi-structured and audio-recorded. Data were analysed using a Framework Approach. Results Participants perceived eliciting ACs as important for: reducing the need for multiple visits, identifying serious illness early, and increasing patient and GP satisfaction. GPs found the prompts easy to use and some continued their use after the study had ended to aid time management. Others noted similarities between the intervention and their usual practice. Nevertheless, soliciting ACs in every consultation was not unanimously supported. Conclusion The prompts were acceptable to GPs within a trial context, but there was disagreement as to whether ACs should be solicited routinely. Some GPs considered the intervention to aid their prioritisation efficiency within consultations. Practice implications Some GPs will find prompts which encourage ACs to be solicited early in the consultation enable them to better organise priorities and manage time-limited consultations more effectively.