1,626 research outputs found

    Chord Label Personalization through Deep Learning of Integrated Harmonic Interval-based Representations

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    The increasing accuracy of automatic chord estimation systems, the availability of vast amounts of heterogeneous reference annotations, and insights from annotator subjectivity research make chord label personalization increasingly important. Nevertheless, automatic chord estimation systems are historically exclusively trained and evaluated on a single reference annotation. We introduce a first approach to automatic chord label personalization by modeling subjectivity through deep learning of a harmonic interval-based chord label representation. After integrating these representations from multiple annotators, we can accurately personalize chord labels for individual annotators from a single model and the annotators' chord label vocabulary. Furthermore, we show that chord personalization using multiple reference annotations outperforms using a single reference annotation.Comment: Proceedings of the First International Conference on Deep Learning and Music, Anchorage, US, May, 2017 (arXiv:1706.08675v1 [cs.NE]

    A Preliminary Investigation Comparing Craniofacial Metric Measurements and 3D Virtual Measurements

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    The development and advancement of new laser scanning techniques enables the capture of 3D imaging which can be quantitatively assessed for use on the human skull. I used a Polhemus Fast Scan Scorpion scanner to scan 8 skulls and evaluated the standard 24 metric measurements in Delta analysis software in comparison to standard metric measurements. The scanned measurements were then compared to the standard metric measurements using the same landmarks. Of the original 48 measurements, 33 (68.75%) fail to reject the null and 10 (20.83%) reject the null with the remaining 5 (10.41%) being unknown due to n=1 because of skull damage. The measurements that proved highly reliable were those associated with specific landmarks, and not those measurements that are based on landmarks and feel and considered arbitrary in this study. This study indicates that the use of the laser scanner can be a useful tool for rapid acquisition of skeletal and anatomical surfaces however, accurate location of landmarks and operator skill are of utmost importance in achieving accurate and reliable results

    Aircraft cost modelling, integrated in a multidisciplinary design context

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    Most of the current cost models focus on a particular manufacturing process or a specific maintenance aspect, therefore not providing the whole picture. The main challenge in modelling the manufacturing cost, associated to a new aircraft at the initial design stage, is to examine all the cost features and the way to link them into the decision making process. It is important to understand the cost related to different competing designs, and this can be tackled by including cost estimation in the design process. Estimating the cost at the early design stage is paramount to reduce the life cycle cost of the aircraft. This paper presents the development of a new methodology for the generation of a cost estimation approach for preliminary aircraft design in a multidisciplinary environment. The framework is able to capture the design attributes that drive the cost allowing a designer to assess cost changes with respect to different design configurations. The cost model is built in Excel using a Visual Basic interface and it is integrated within Model Centre platform, where it can be treated as a component of a computational design process. The paper concludes by presenting the results from a real wing trade-off study that includes all the components of a complete design system

    Research and Technology

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    Langley Research Center is engaged in the basic an applied research necessary for the advancement of aeronautics and space flight, generating advanced concepts for the accomplishment of related national goals, and provding research advice, technological support, and assistance to other NASA installations, other government agencies, and industry. Highlights of major accomplishments and applications are presented

    Harmonic Change Detection from Musical Audio

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    In this dissertation, we advance an enhanced method for computing Harte et al.’s [31] Harmonic Change Detection Function (HCDF). HCDF aims to detect harmonic transitions in musical audio signals. HCDF is crucial both for the chord recognition in Music Information Retrieval (MIR) and a wide range of creative applications. In light of recent advances in harmonic description and transformation, we depart from the original architecture of Harte et al.’s HCDF, to revisit each one of its component blocks, which are evaluated using an exhaustive grid search aimed to identify optimal parameters across four large style-specific musical datasets. Our results show that the newly proposed methods and parameter optimization improve the detection of harmonic changes, by 5.57% (f-score) with respect to previous methods. Furthermore, while guaranteeing recall values at > 99%, our method improves precision by 6.28%. Aiming to leverage novel strategies for real-time harmonic-content audio processing, the optimized HCDF is made available for Javascript and the MAX and Pure Data multimedia programming environments. Moreover, all the data as well as the Python code used to generate them, are made available.<br /

    Sex estimation through discriminant function analysis of an archaeological population from Mistihalj, Montenegro

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    Thesis (M.S.)--Boston UniversityIn an effort to create discriminant function equations for a spatially and temporally specific archaeological population, this study utilized metric analyses of the crania and post-crania in a collection from Mistihalj, Montenegro housed at the Peabody Museum of Archaeology and Ethnology. After the data was collected, discriminant function analyses were performed and used in the creation of univariate and multivariate sectioning points for the purpose of estimating the sex of archaeological populations in this region. It is believed that the equations created will supplement other bioarchaeological methods for sex estimation within archaeological populations of the Balkan region where single skeletal elements or commingled remains may be prominent. This project will also provide a better understanding of sexual dimorphism in Balkan populations, which may ultimately help when working to make a biological profile for an unknown individual in this region. The best univariate measures for sex estimation (ranging from 96% to 85% accuracy) are: maximum diameter of the femur head, sagittal diameter of the radius at midshaft, maximum length of the ulna, maximum vertical diameter of the head of the humerus, biauricular breadth, maximum length of the radius, epicondylar breadth of the femur, anterio-posterior diameter of the femur at midshaft, maximum length of the humerus, maximum length of the calcaneus, bizygomatic breadth, and maximum epiphyseal breadth of the proximal tibia. All multivariate equations achieved classification rates above 85%. The best elements for multivariate analysis (above 90% accuracy) are: femur, radius, humerus, cranium, tibia, and ulna. Unexpectedly, two cranial measures are among the most accurate univariate measures, and the cranium provided higher classification rates than expected in comparison to post-cranial elements in the multivariate analyses. The multivariate equations created are only applicable if every measure/landmark required is present on the skeleton in question. As there is often differential preservation of skeletal elements, the use of multiple univariate sectioning points may be better on moderately or very poorly preserved remains

    Leveraging repetition for improved automatic lyric transcription in popular music

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    Transcribing lyrics from musical audio is a challenging research prob-lem which has not benefited from many advances made in the related field of automatic speech recognition, owing to the prevalent musical accompaniment and differences between the spoken and sung voice. However, one aspect of this problem which has yet to be exploited by researchers is that significant portions of the lyrics will be repeated throughout the song. In this paper we investigate how this information can be leveraged to form a consensus transcription with improved consistency and accuracy. Our results show that improvements can be gained using a variety of techniques, and that relative gains are largest under the most challenging and realistic experimental conditions
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