Reactive Statistical Mapping: Towards the Sketching of Performative Control with Data

Part 1: Fundamental IssuesInternational audienceThis paper presents the results of our participation to the ninth eNTERFACE workshop on multimodal user interfaces. Our target for this workshop was to bring some technologies currently used in speech recognition and synthesis to a new level, i.e. being the core of a new HMM-based mapping system. The idea of statistical mapping has been investigated, more precisely how to use Gaussian Mixture Models and Hidden Markov Models for realtime and reactive generation of new trajectories from inputted labels and for realtime regression in a continuous-to-continuous use case. As a result, we have developed several proofs of concept, including an incremental speech synthesiser, a software for exploring stylistic spaces for gait and facial motion in realtime, a reactive audiovisual laughter and a prototype demonstrating the realtime reconstruction of lower body gait motion strictly from upper body motion, with conservation of the stylistic properties. This project has been the opportunity to formalise HMM-based mapping, integrate various of these innovations into the Mage library and explore the development of a realtime gesture recognition tool

Study on scale development for individual instrument practice habits in musical education

Çalışmanın amacı, müzik eğitiminin önemli bir boyutu olan çalgı eğitiminde, öğrencilerin çalışma alışkanlıkları düzeylerini belirleyecek bir ölçek geliştirmek ve geliştirilen bu ölçeğin geçerlikgüvenirlik çalışmasını yapmaktır. Ölçek 18 maddeden oluşmuştur. Ölçeğin yapı geçerliği faktör analizi ile incelenmiş ve elde edilen bulgular doğrultusunda ölçeğin 4 faktörlü olduğu tespit edilmiştir. Döndürülmüş bileşenler matrisi analizi sonuçlarına göre ölçek maddelerinin KaiserMeyer-Olkin değeri .925 ve Barlett testi sonucu anlamlı bulunmuş (p .05), ki kare değeri 4159.217, df256 elde edilmesi verilerin açımlayıcı faktör analizine uygunluğunu belirlenmiştir. Ölçeğin bütün maddelerini içeren Croncbah's Alpha güvenirlik kat sayısı .891 bulunmuştur. Sonuç olarak ölçeğin öğrencilerin bireysel çalgı çalışma alışkanlıkları düzeylerinin belirlenmesinde güvenle kullanılabileceği tespit edilmiştir.The purpose of the study is to develop a scale that can determine students' practice habit levels in instrument training, an important aspect in musical education, and to study the validity-reliability of the developed scale. The scale is comprised of 18 items. The structural reliability of the scale was examined with factor analysis, and, in line with the findings, the scale has 4 factors. According to the rotated components matrix analysis results, the Kaiser-Meyer-Olkin value of scale items was .925; thee Barlett test result was found to be significant (p>.05); and the x-square value4159.217, df256 obtained determined that data is appropriate for exploratory factor analysis. The Cronbach Alpha reliability coefficient, which includes all items of the scale, was calculated as .891. As a result, we found that the scale can be reliably used for determining the levels of individual instrument practice habits of students

A Quantitative Comparison of Glottal Closure Instant Estimation Algorithms on a Large Variety of Singing Sounds

Glottal closure instant (GCI) estimation is a well-studied topic that plays a critical role in several speech processing applications. Many GCI estimation algorithms have been proposed in the literature and shown to provide excellent results on the speech signal. Nonetheless the efficiency of these algorithms for the analysis of the singing voice is still unknown. The goal of this paper is to assess the performance of existing GCI estimation methods on the singing voice with a quantitative comparison. A second goal is to provide a starting point for the adaptation of these algorithms to the singing voice by identifying weaknesses and strengths under different conditions. This study is carried out on a large database of singing sounds with synchronous electroglottography (EGG) recordings, containing a variety of singer categories and singing techniques. The evaluated algorithms are Dynamic Programming Phase Slop

A COMPARATIVE STUDY OF PITCH EXTRACTION ALGORITHMS ON A LARGE VARIETY OF SINGING SOUNDS

The problem of pitch tracking has been extensively studied in the speech research community. The goal of this paper is to investigate how these techniques should be adapted to singing voice analysis, and to provide a comparative evaluation of the most representative state-of-the-art approaches. This study is carried out on a large database of annotated singing sounds with aligned EGG recordings, comprising a variety of singer categories and singing exercises. The algorithmic performance is assessed according to the ability to detect voicing boundaries and to accurately estimate pitch contour. First, we evaluate the usefulness of adapting existing methods to singing voice analysis. Then we compare the accuracy of several pitchextractio