EMIF: Towards a scalable and effective indexing framework for large scale music retrieval

Microsoft Research Asia Gran

Toward efficient indexing structure for scalable content-based music retrieval

Pretendemos problematizar arte e loucura, inicialmente discutindo a experiência do pesquisador em relação às imagens do mundo, com o testemunho e a figura do louco e, consequentemente, com o fora que ela evoca. Em seguida nos colocamos diante do muro, situação-limite na qual a loucura enquanto catástrofe e a arte enquanto via poética vêm compor um limiar, ausência que Blanchot transpõe à linguagem para dar a ver outras constelações possíveis, tanto de palavras quanto de seus inomináveis. Por fim, com Walter Benjamin, pomos a história da loucura a contrapelo, e, mergulhados no Ateliê de Escrita do Hospital Psiquiátrico São Pedro, desvelamos que a arte pode, na relação com a loucura, tornar-se a linguagem essencial na perigosa travessia em direção à experiência, transpondo a vivência desse estado assustador para trazer ao mundo outro sentido, reconhecendo outros modos de existência que podem vir a ser outras poéticas de vida.We intend to problematize art and madness. We begin by discussing the experience of the researcher in relation to images of the world, to witnessing and to the image of the insane, and then inevitably to the outside they evoke. Subsequently, we stand before a wall, a limit situation in which madness as catastrophe and art as poetics compose a threshold, an absence which Blanchot transposes to language to bring other possible constellations into view, both as words and as their unnamable others. Finally, with Walter Benjamin, we touch upon the grain of the history of madness – immersed in the Writing Workshop at the São Pedro Psychiatric Hospital, in Porto Alegre, Brazil, we reveal that, in relation to madness, art can become the essential language of the perilous passage towards experience, transposing the experience of this horrific state to bring another sense to the world, recognizing other modes of existence which may come to be other poetics of life.Nous désirons problématiser l’art et la folie, initialement en discutant l’expérience du chercheur par rapport aux images du monde, avec le témoignage et l’image du fou, et, par conséquent, l’extérieur qu’elle évoque. Puis, on se pose devant le mur, situation extrême dans laquelle la folie comme catastrophe et l’art comme voie poétique composent un seuil viennent à construire un seuil, absence que Blanchot transpose en langage afin de révéler d’autres constellations possibles tant comme des mots, tant comme ses innombrables. Enfin, avec Walter Benjamin, nous prenons l’histoire de la folie à contre-poil, et plongés dans l’Atelier d’écriture de l’Hôpital psychiatrique de São Pedro, à Porto Alegre au Brésil, nous révélons que l’art, par rapport à la folie, peut devenir le langage essentiel de la traversée dangereuse vers l’expérience, en transposant le vécu de cet état terrifiant, afin de donner un autre sens au monde, tout en reconnaissant d’autres modes d’existence qui pourraient devenir d’autres poétiques de vie.Nuestra intención es de problematizar el arte y la locura, inicialmente discutiendo la experiencia del investigador en relación con las imágenes del mundo, el testimonio y la figura del loco, y por lo tanto con el afuera que ella evoca. Seguidamente, nos ponemos delante de un muro, una situación extrema en la que la locura como catástrofe y el arte como vía poética componen un umbral, una ausencia que Blanchot transpone en lenguaje para revelar las otras constelaciones posibles tanto como palabras, tanto como innombrables otros. Por último, con Walter Benjamin, ponemos la historia de la locura a contra pelo, y sumergidos en el Taller de escritura del Hospital Psiquiátrico São Pedro de Porto Alegre, Brasil, desvelamos que, en relación con la locura, el arte puede convertirse en el lenguaje esencial de ese peligroso pasaje que nos conduce a la experiencia, que transpone lo vivido en este estado aterrador para dar otro sentido al mundo, reconociendo otros modos de existencia que pueden llegar a ser otras poéticas de vida

A computational study on outliers in world music

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country

Unknowingly knowing the unknown - exploring the MMN of statistical language learning in a natural linguistic context

Statistisk læring (SL) er ein kjernemekanisme i språklæring. SL har vorte undersøkt i både åtferdsbaserte og nevrofysiologiske eksperiment. I det fylgjande vil me presentera rammene for eit EEG-eksperiment kor tjue deltakarar (ukyndige i russisk eller andre slaviske språk) fekk høyre ein talestraum med russiske ord, kor seks moglege rotord var sett saman med to moglege endingar. Kort fortalt var målet for studien å undersøka om eksponering for naturleg språkstimuli utløyste ein nevrofysiologisk markør for regeltileigning gjennom statistisk læring som kallast statistical mismatch negativity (sMMN). Eit anna mål var å undersøka om deltakarane opplevde læring. Dette dokumentet inneheld kappe og artikkel for studien.Masteroppgåve i logopediLOGO345MAPS-LOG0

Error Signals from the Brain: 7th Mismatch Negativity Conference

The 7th Mismatch Negativity Conference presents the state of the art in methods, theory, and application (basic and clinical research) of the MMN (and related error signals of the brain). Moreover, there will be two pre-conference workshops: one on the design of MMN studies and the analysis and interpretation of MMN data, and one on the visual MMN (with 20 presentations). There will be more than 40 presentations on hot topics of MMN grouped into thirteen symposia, and about 130 poster presentations. Keynote lectures by Kimmo Alho, Angela D. Friederici, and Israel Nelken will round off the program by covering topics related to and beyond MMN

A COMPUTATION METHOD/FRAMEWORK FOR HIGH LEVEL VIDEO CONTENT ANALYSIS AND SEGMENTATION USING AFFECTIVE LEVEL INFORMATION

VIDEO segmentation facilitates e±cient video indexing and navigation in large digital video archives. It is an important process in a content-based video indexing and retrieval (CBVIR) system. Many automated solutions performed seg- mentation by utilizing information about the \facts" of the video. These \facts" come in the form of labels that describe the objects which are captured by the cam- era. This type of solutions was able to achieve good and consistent results for some video genres such as news programs and informational presentations. The content format of this type of videos is generally quite standard, and automated solutions were designed to follow these format rules. For example in [1], the presence of news anchor persons was used as a cue to determine the start and end of a meaningful news segment. The same cannot be said for video genres such as movies and feature films. This is because makers of this type of videos utilized different filming techniques to design their videos in order to elicit certain affective response from their targeted audience. Humans usually perform manual video segmentation by trying to relate changes in time and locale to discontinuities in meaning [2]. As a result, viewers usually have doubts about the boundary locations of a meaningful video segment due to their different affective responses. This thesis presents an entirely new view to the problem of high level video segmentation. We developed a novel probabilistic method for affective level video content analysis and segmentation. Our method had two stages. In the first stage, a®ective content labels were assigned to video shots by means of a dynamic bayesian 0. Abstract 3 network (DBN). A novel hierarchical-coupled dynamic bayesian network (HCDBN) topology was proposed for this stage. The topology was based on the pleasure- arousal-dominance (P-A-D) model of a®ect representation [3]. In principle, this model can represent a large number of emotions. In the second stage, the visual, audio and a®ective information of the video was used to compute a statistical feature vector to represent the content of each shot. Affective level video segmentation was achieved by applying spectral clustering to the feature vectors. We evaluated the first stage of our proposal by comparing its emotion detec- tion ability with all the existing works which are related to the field of a®ective video content analysis. To evaluate the second stage, we used the time adaptive clustering (TAC) algorithm as our performance benchmark. The TAC algorithm was the best high level video segmentation method [2]. However, it is a very computationally intensive algorithm. To accelerate its computation speed, we developed a modified TAC (modTAC) algorithm which was designed to be mapped easily onto a field programmable gate array (FPGA) device. Both the TAC and modTAC algorithms were used as performance benchmarks for our proposed method. Since affective video content is a perceptual concept, the segmentation per- formance and human agreement rates were used as our evaluation criteria. To obtain our ground truth data and viewer agreement rates, a pilot panel study which was based on the work of Gross et al. [4] was conducted. Experiment results will show the feasibility of our proposed method. For the first stage of our proposal, our experiment results will show that an average improvement of as high as 38% was achieved over previous works. As for the second stage, an improvement of as high as 37% was achieved over the TAC algorithm

Representation of speech in the primary auditory cortex and its implications for robust speech processing

Speech has evolved as a primary form of communication between humans. This most used means of communication has been the subject of intense study for years, but there is still a lot that we do not know about it. It is an oft repeated fact, that even the performance of the best speech processing algorithms still lags far behind that of the average human, It seems inescapable that unless we know more about the way the brain performs this task, our machines can not go much further. This thesis focuses on the question of speech representation in the brain, both from a physiological and technological perspective. We explore the representation of speech through the encoding of its smallest elements - phonemic features - in the primary auditory cortex. We report on how population of neurons with diverse tuning properties respond discriminately to phonemes resulting in explicit encoding of their parameters. Next, we show that this sparse encoding of the phonemic features is a simple consequence of the linear spectro-temporal properties of the auditory cortical neurons and that a Spectro-Temporal receptive field model can predict similar patterns of activation. This is an important step toward the realization of systems that operate based on the same principles as the cortex. Using an inverse method of reconstruction, we shall also explore the extent to which phonemic features are preserved in the cortical representation of noisy speech. The results suggest that the cortical responses are more robust to noise and that the important features of phonemes are preserved in the cortical representation even in noise. Finally, we explain how a model of this cortical representation can be used for speech processing and enhancement applications to improve their robustness and performance