Speech

This dataset contains source and processed audio files designed primarily for use with Time-Scale Modification (TSM) research.  88 source files were processed at 10 different time-scale ratios by 6 different TSM algorithms resulting in training set of 5280 files.  Each file was then subjectively evaluated by a minimum of 7 participants providing opinion scores.  Mean Opinion Scores (MeanOS) and Median Opinion Scores (MedianOS) are provided for each file.  An additional 20 files were processed at 4 time-scale ratios by an additional 3 methods were also subjectively evaluated resulting in a t

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  • Machine Learning
  • Last Updated On: 
    Thu, 01/09/2020 - 02:31

    Our efforts are made on one-shot voice conversion where the target speaker is unseen in training dataset or both source and target speakers are unseen in the training dataset. In our work, StarGAN is employed to carry out voice conversation between speakers. An embedding vector is used to represent speaker ID. This work relies on two datasets in English and one dataset in Chinese, involving 38 speakers. A user study is conducted to validate our framework in terms of reconstruction quality and conversation quality.

    111 views
  • Machine Learning
  • Last Updated On: 
    Tue, 10/22/2019 - 21:40

    The dataset consists of EEG recordings obtained when subjects are listening to different utterances : a, i, u, bed, please, sad. A limited number of EEG recordings where also obtained when the three vowels were corrupted by white and babble noise at an SNR of 0dB. Recordings were performed on 8 healthy subjects.

    398 views
  • Brain
  • Last Updated On: 
    Mon, 08/12/2019 - 11:24

    This dataset is associated with the paper, Giovanni Dimauro et al. 2017, which is open source, and can be found here: https://ieeexplore.ieee.org/document/8070308

    The DataPort Repository contains the data used primarily for generating Figure 2,3,4,5

    235 views
  • Biomedical and Health Sciences
  • Last Updated On: 
    Tue, 06/11/2019 - 04:31