352 resultados para Audio indexing


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Visual information in the form of lip movements of the speaker has been shown to improve the performance of speech recognition and search applications. In our previous work, we proposed cross database training of synchronous hidden Markov models (SHMMs) to make use of external large and publicly available audio databases in addition to the relatively small given audio visual database. In this work, the cross database training approach is improved by performing an additional audio adaptation step, which enables audio visual SHMMs to benefit from audio observations of the external audio models before adding visual modality to them. The proposed approach outperforms the baseline cross database training approach in clean and noisy environments in terms of phone recognition accuracy as well as spoken term detection (STD) accuracy.

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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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Speech recognition can be improved by using visual information in the form of lip movements of the speaker in addition to audio information. To date, state-of-the-art techniques for audio-visual speech recognition continue to use audio and visual data of the same database for training their models. In this paper, we present a new approach to make use of one modality of an external dataset in addition to a given audio-visual dataset. By so doing, it is possible to create more powerful models from other extensive audio-only databases and adapt them on our comparatively smaller multi-stream databases. Results show that the presented approach outperforms the widely adopted synchronous hidden Markov models (HMM) trained jointly on audio and visual data of a given audio-visual database for phone recognition by 29% relative. It also outperforms the external audio models trained on extensive external audio datasets and also internal audio models by 5.5% and 46% relative respectively. We also show that the proposed approach is beneficial in noisy environments where the audio source is affected by the environmental noise.

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Automated digital recordings are useful for large-scale temporal and spatial environmental monitoring. An important research effort has been the automated classification of calling bird species. In this paper we examine a related task, retrieval of birdcalls from a database of audio recordings, similar to a user supplied query call. Such a retrieval task can sometimes be more useful than an automated classifier. We compare three approaches to similarity-based birdcall retrieval using spectral ridge features and two kinds of gradient features, structure tensor and the histogram of oriented gradients. The retrieval accuracy of our spectral ridge method is 94% compared to 82% for the structure tensor method and 90% for the histogram of gradients method. Additionally, this approach potentially offers a more compact representation and is more computationally efficient.

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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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Access to transport systems and the connection to such systems provided to essential economic and social activities are critical to determine households' transportation disadvantage levels. In spite of the developments in better identifying transportation disadvantaged groups, the lack of effective policies resulted in the continuum of the issue as a significant problem. This paper undertakes a pilot case investigation as test bed for a new approach developed to reduce transportation policy shortcomings. The approach, ‘disadvantage-impedance index’, aims to ease transportation disadvantages by employing representative parameters to measure the differences between policy alternatives run in a simulation environment. Implemented in the Japanese town of Arao, the index uses trip-making behaviour and resident stated preference data. The results of the index reveal that even a slight improvement in accessibility and travel quality indicators makes a significant difference in easing disadvantages. The index, integrated into a four-step model, proves to be highly robust and useful in terms of quick diagnosis in capturing effective actions, and developing potentially efficient policies.

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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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Acoustic recordings play an increasingly important role in monitoring terrestrial and aquatic environments. However, rapid advances in technology make it possible to accumulate thousands of hours of recordings, more than ecologists can ever listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from minutes, hours, days to years. The visualization should facilitate navigation and yield ecologically meaningful information prior to listening to the audio. To construct images, we calculate acoustic indices, statistics that describe the distribution of acoustic energy and reflect content of ecological interest. We combine various indices to produce false-color spectrogram images that reveal acoustic content and facilitate navigation. The technical challenge we investigate in this work is how to navigate recordings that are days or even months in duration. We introduce a method of zooming through multiple temporal scales, analogous to Google Maps. However, the “landscape” to be navigated is not geographical and not therefore intrinsically visual, but rather a graphical representation of the underlying audio. We describe solutions to navigating spectrograms that range over three orders of magnitude of temporal scale. We make three sets of observations: 1. We determine that at least ten intermediate scale steps are required to zoom over three orders of magnitude of temporal scale; 2. We determine that three different visual representations are required to cover the range of temporal scales; 3. We present a solution to the problem of maintaining visual continuity when stepping between different visual representations. Finally, we demonstrate the utility of the approach with four case studies.

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Background Australian policy mandates consumer and carer participation in mental health services at all levels including research. Inspired by a UK model - Service Users Group Advising on Research [SUGAR] - we conducted a scoping project in 2013 with a view to create a consumer and carer led research process that moves beyond stigma and tokenism, that values the unique knowledge of lived experience and leads to people being treated better when accessing services. This poster presents the initial findings. Aims The project’s purpose was to explore with consumers, consumer companions and carers at the Metro North Mental Health-RBWH their interest in and views about research partnerships with academic and clinical colleagues. Methods This poster overviews the initial findings from three audio-recorded focus groups conducted with a total of 14 consumers, carers and consumer companions at the Brisbane site. Analysis Our work was guided by framework analysis (Gale et al. 2013). It defines 5 steps for analysing narrative data: familiarising; development of categories; indexing; charting and interpretation. Eight main ideas were initially developed and were divided between the authors to further index. This process identified 37 related analytic ideas. The authors integrated these by combining, removing and redefining them by consensus though a mapping process. The final step is the return of the analysis to the participants for feedback and input into the interpretation of the focus group discussions. Results 1. Value & Respect: Feeling Valued & Respected, Tokenism, Stigma, Governance, Valuing prior knowledge / background 2. Pathways to Knowledge and Involvement in Research: ‘Where to begin’, Support, Unity & partnership, Communication, Co-ordination, Flexibility due to fluctuating capacity 3. Personal Context: Barriers regarding Commitments & the nature of mental illness, Wellbeing needs, Prior experience of research, Motivators, Attributes 4. What is research? Developing Knowledge, What to do research on, how and why? Conclusion and Discussion Initial analysis suggests that participants saw potential for ‘amazing things’ in mental health research such as reflecting their priorities and moving beyond stigma and tokenism. The main needs identified were education, mentoring, funding support and research processes that fitted consumers’ and carers’limitations and fluctuating capacities. They identified maintaining motivation and interest as an issue since research processes are often extended by ethics and funding applications. Participants felt that consumer and carer led research would value the unique knowledge that the lived experience of consumers and carers brings and lead to people being treated better when accessing services.

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The aim of this paper is to present results of research investigating the effectiveness of audio feedback in a third year undergraduate unit. While there is a large and growing body of literature about providing assessment feedback, there is little focussing on the use of audio media. This study employs a mixed method approach, involving semi-structured interviews with academic staff and a survey of students. Analysis of the interview data suggests that there are a number of issues surrounding acceptance of using audio feedback by lecturers. The next stage of the study is to examine the extent to which lecturers change their perceptions as they use audio feedback and to analyse the perceptions of the students (n=120), including the perceived importance of feedback, the ways in which they used the audio feedback and the extent to which they believe they control events that affect them. Ultimately, this study seeks to provide recommendations appropriate to the implementation of audio feedback in higher education.

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Providing audio feedback to assessment is relatively uncommon in higher education. However, published research suggests that it is preferred over written feedback by students but lecturers were less convinced. The aim of this paper is to examine further these findings in the context of a third year business ethics unit. Data was collected from two sources. The first is a series of in-depth, semi-structured interviews conducted with three lecturers providing audio feeback for the first time in Semester One 2011. The second source of data was drawn from the university student evaluation system. A total of 363 responses were used providing 'before' and 'after' perspectives about the effectiveness of audio feedback versus written feedback. Between 2005 and 2009 the survey data provided information about student attitudes to written assessment feedback (n=261). From 2010 onwards the data relates to audio (mp3) feedback (n=102). The analysis of he interview data indicated that introducing audio feedback should be done with care. The perception of the participating lecturers was mixed, ranging from sceptism to outright enthusiasm, but over time the overall approach became positive. It was found that particular attention needs to be paid to small (but important) technical details, and lecturers need to be convinced of its effectieness, especially that it is not necessarily more time consuming than providing written feedback. For students, the analysis revealed a clear preference for audio feedback. It is concluded that there is cause for concern and reason for optimism. It is a cause for concern because there is a possibility that scepticism on the part of academic staff seems to be based on assumptions about what students prefer and a concern about using the technology. There is reason for optimism because the evidence points towards students preferring audio feedback and as academic staff become more familiar with the technology the scepticism tends to evaporate. While this study is limited in scope, questions are raised about tackling negative staff perceptions of audio feedback that are worthy of further research.

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This research investigates techniques to analyse long duration acoustic recordings to help ecologists monitor birdcall activities. It designs a generalized algorithm to identify a broad range of bird species. It allows ecologists to search for arbitrary birdcalls of interest, rather than restricting them to just a very limited number of species on which the recogniser is trained. The algorithm can help ecologists find sounds of interest more efficiently by filtering out large volumes of unwanted sounds and only focusing on birdcalls.

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In recent years, many of the world’s leading media producers, screenwriters, technicians and investors, particularly those in the Asia-Pacific region, have been drawn to work in the People's Republic of China (hereafter China or Mainland China). Media projects with a lighter commercial entertainment feel – compared with the heavy propaganda-oriented content of the past – have multiplied, thanks to the Chinese state’s newfound willingness to consider collaboration with foreign partners. This is no more evident than in film. Despite their long-standing reputation for rigorous censorship, state policymakers are now encouraging Chinese media entrepreneurs to generate fresh ideas and to develop products that will revitalise the stagnant domestic production sector. It is hoped that an increase in both the quality and quantity of domestic feature films, stimulated by an infusion of creativity and cutting-edge technology from outside the country, will help reverse China’s ‘cultural trade deficit’ (wenhua maoyi chizi) (Keane 2007).

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The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.

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Teachers' failure to utilise MBL activities more widely may be due to not recognising their capacity to transform the nature of laboratory activities to be more consistent with contemporary constructivist theories of learning. This research aimed to increase understanding of how MBL activities specifically designed to be consistent with a constructivist theory of learning support or constrain student construction of understanding. The first author conducted the research with his Year 11 physics class of 29 students. Dyads completed nine tasks relating to kinematics using a Predict-Observe-Explain format. Data sources included video and audio recordings of students and teacher during four 70-minute sessions, students' display graphs and written notes, semi-structured student interviews, and the teacher's journal. The study identifies the actors and describes the patterns of interactions in the MBL. Analysis of students' discourse and actions identified many instances where students' initial understanding of kinematics were mediated in multiple ways. Students invented numerous techniques for manipulating data in the service of their emerging understanding. The findings are presented as eight assertions. Recommendations are made for developing pedagogical strategies incorporating MBL activities which will likely catalyse student construction of understanding.