News & Events

56 MERL Events and MERL Talks found.


  •  TALK    Tensor representation of speaker space for arbitrary speaker conversion
    Date & Time: Thursday, September 6, 2012; 12:00 PM
    Speaker: Dr. Daisuke Saito, The University of Tokyo
    Research Area: Speech & Audio
    Abstract
    • In voice conversion studies, realization of conversion from/to an arbitrary speaker's voice is one of the important objectives. For this purpose, eigenvoice conversion (EVC) based on an eigenvoice Gaussian mixture model (EV-GMM) was proposed. In the EVC, similarly to speaker recognition approaches, a speaker space is constructed based on GMM supervectors which are high-dimensional vectors derived by concatenating the mean vectors of each of the speaker GMMs. In the speaker space, each speaker is represented by a small number of weight parameters of eigen-supervectors. In this talk, we revisit construction of the speaker space by introducing the tensor analysis of training data set. In our approach, each speaker is represented as a matrix of which the row and the column respectively correspond to the Gaussian component and the dimension of the mean vector, and the speaker space is derived by the tensor analysis of the set of the matrices. Our approach can solve an inherent problem of supervector representation, and it improves the performance of voice conversion. Experimental results of one-to-many voice conversion demonstrate the effectiveness of the proposed approach.
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  •  TALK    Learning Intermediate-Level Representations of Form and Motion from Natural Movies
    Date & Time: Wednesday, February 22, 2012; 11:00 AM
    Speaker: Dr. Charles Cadieu, McGovern Institute for Brain Research, MIT
    MERL Host: Jonathan Le Roux
    Research Area: Speech & Audio
    Abstract
    • The human visual system processes complex patterns of light into a rich visual representation where the objects and motions of our world are made explicit. This remarkable feat is performed through a hierarchically arranged series of cortical areas. Little is known about the details of the representations in the intermediate visual areas. Therefore, we ask the question: can we predict the detailed structure of the representations we might find in intermediate visual areas?

      In pursuit of this question, I will present a model of intermediate-level visual representation that is based on learning invariances from movies of the natural environment and produces predictions about intermediate visual areas. The model is composed of two stages of processing: an early feature representation layer, and a second layer in which invariances are explicitly represented. Invariances are learned as the result of factoring apart the temporally stable and dynamic components embedded in the early feature representation. The structure contained in these components is made explicit in the activities of second-layer units that capture invariances in both form and motion. When trained on natural movies, the first-layer produces a factorization, or separation, of image content into a temporally persistent part representing local edge structure and a dynamic part representing local motion structure. The second-layer units are split into two populations according to the factorization in the first-layer. The form-selective units receive their input from the temporally persistent part (local edge structure) and after training result in a diverse set of higher-order shape features consisting of extended contours, multi-scale edges, textures, and texture boundaries. The motion-selective units receive their input from the dynamic part (local motion structure) and after training result in a representation of image translation over different spatial scales and directions, in addition to more complex deformations. These representations provide a rich description of dynamic natural images, provide testable hypotheses regarding intermediate-level representation in visual cortex, and may be useful representations for artificial visual systems.
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  •  TALK    Auxiliary Function Approach to Source Localization and Separation
    Date & Time: Thursday, October 20, 2011; 3:40 PM
    Speaker: Prof. Nobutaka Ono, National Institute of Informatics, Tokyo
    MERL Host: Jonathan Le Roux
    Research Area: Speech & Audio
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  •  TALK    Itakura-Saito nonnegative matrix factorization and friends for music signal decomposition
    Date & Time: Thursday, October 20, 2011; 3:00 PM
    Speaker: Dr. Cedric Fevotte, CNRS - Telecom ParisTech, Paris
    MERL Host: Jonathan Le Roux
    Research Area: Speech & Audio
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  •  TALK    Analysing Digital Music
    Date & Time: Thursday, October 20, 2011; 2:20 PM
    Speaker: Prof. Mark Plumbley, Queen Mary, London
    MERL Host: Jonathan Le Roux
    Research Area: Speech & Audio
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  •  EVENT    Audio and Music Signal Processing Mini-Symposium
    Date & Time: Thursday, October 20, 2011; 2:00 PM -5:00 PM
    Location: MERL
    MERL Contact: Jonathan Le Roux
    Research Area: Speech & Audio
    Brief
    • MERL is hosting a mini-symposium on audio and music signal processing, with three talks by eminent researchers in the field: Prof. Mark Plumbley, Dr. Cedric Fevotte and Prof. Nobutaka Ono.
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