Blar i NTNU Open på forfatter "Siniscalchi, Sabato Marco"

Viser treff 1-7 av 7

    • Acoustic-to-Articulatory Mapping With Joint Optimization of Deep Speech Enhancement and Articulatory Inversion Models 

      Sabzi Shahrebabaki, Abdolreza; Salvi, Giampiero; Svendsen, Torbjørn Karl; Siniscalchi, Sabato Marco (Journal article; Peer reviewed, 2021)
      We investigate the problem of speaker independent acoustic-to-articulatory inversion (AAI) in noisy conditions within the deep neural network (DNN) framework. In contrast with recent results in the literature, we argue ...

    • Articulatory Inversion for Speech Technology Applications 

      Shahrebabaki, Abdolreza Sabzi (Doctoral theses at NTNU;2022:198, Doctoral thesis, 2022)
      Within the past decades advances in neural networks have improved the performance of a vast area of speech processing applications including the articulatory inversion problem which is concerned with estimating the vocal ...

    • A DNN Based Speech Enhancement Approach to Noise Robust Acoustic-to-Articulatory Inversion 

      Sabzi Shahrebabaki, Abdolreza; Siniscalchi, Sabato Marco; Salvi, Giampiero; Svendsen, Torbjørn Karl (Chapter, 2021)
      In this work, we investigate the problem of speaker independent acoustic-to-articulatory inversion (AAI) in noisy condition within the deep neural network (DNN) framework. We claim that DNN vector-to-vector regression for ...

    • Sequence-to-sequence articulatory inversion through time convolution of sub-band frequency signals 

      Sabzi Shahrebabaki, Abdolreza; Siniscalchi, Sabato Marco; Salvi, Giampiero; Svendsen, Torbjørn Karl (Peer reviewed; Journal article, 2020)
      We propose a new acoustic-to-articulatory inversion (AAI) sequence-to-sequence neural architecture, where spectral sub-bands are independently processed in time by 1-dimensional (1-D) convolutional filters of different ...

    • A step-by-step training method for multi generator GANs with application to anomaly detection and cybersecurity 

      Adiban, Mohammad; Siniscalchi, Sabato Marco; Salvi, Giampiero (Peer reviewed; Journal article, 2023)
      Cyber attacks and anomaly detection are problems where the data is often highly unbalanced towards normal observations. Furthermore, the anomalies observed in real applications may be significantly different from the ones ...

    • Transfer learning of articulatory information through phone information. 

      Sabzi Shahrebabaki, Abdolreza; Olfati, Negar; Siniscalchi, Sabato Marco; Salvi, Giampiero; Svendsen, Torbjørn Karl (Journal article; Peer reviewed, 2020)
      Articulatory information has been argued to be useful for several speech tasks. However, in most practical scenarios this information is not readily available. We propose a novel transfer learning framework to obtain ...

    • A Two-Stage Deep Modeling Approach to Articulatory Inversion 

      Sabzi Shahrebabaki, Abdolreza; Olfati, Negar; Imran, Ali Shariq; Johnsen, Magne Hallstein; Siniscalchi, Sabato Marco; Svendsen, Torbjørn Karl (Chapter, 2021)
      This paper proposes a two-stage deep feed-forward neural network (DNN) to tackle the acoustic-to-articulatory inversion (AAI) problem. DNNs are a viable solution for the AAI task, but the temporal continuity of the estimated ...