Dataset Open Access

Multilingual bottle-neck feature learning from untranscribed speech for track 1 in zerospeech2017 (system 2 -- with VTLN)

Hongjie Chen Chen; Cheung-Chi Leung; Lei Xie; Bin Ma; Haizhou Li


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.822737", 
  "title": "Multilingual bottle-neck feature learning from untranscribed speech for track 1 in zerospeech2017 (system 2 -- with VTLN)", 
  "issued": {
    "date-parts": [
      [
        2017, 
        7, 
        4
      ]
    ]
  }, 
  "abstract": "<p>We investigate the extraction of bottle-neck features (BNFs) for multiple languages without access to manual transcription.\u00a0Multilingual BNFs are derived from a multi-task learning deep neural network which is trained with unsupervised phoneme-like labels. The unsupervised phoneme-like labels are obtained from language-dependent Dirichlet process Gaussian mixture models separately trained on untranscribed speech of multiple languages.</p>\n\n<blockquote>\n<p>In this version, the input MFCC for DPGMM is processed with VTLN.</p>\n</blockquote>\n\n<p>\u00a0</p>", 
  "author": [
    {
      "family": "Hongjie Chen Chen"
    }, 
    {
      "family": "Cheung-Chi Leung"
    }, 
    {
      "family": "Lei Xie"
    }, 
    {
      "family": "Bin Ma"
    }, 
    {
      "family": "Haizhou Li"
    }
  ], 
  "type": "dataset", 
  "id": "822737"
}
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