Blar i Institutt for elektroniske systemer på forfatter "Olfati, Negar"

Viser treff 1-5 av 5

    • A Comparative Study of Deep Learning Techniques on Frame-Level Speech Data Classification 

      Sabzi Shahrebabaki, Abdolreza; Imran, Ali Shariq; Olfati, Negar; Svendsen, Torbjørn Karl (Journal article; Peer reviewed, 2019)
      This paper provides a comprehensive analysis of the effect of speaking rate on frame classification accuracy. Different speaking rates may affect the performance of the automatic speech recognition system yielding poor ...

    • Acoustic Feature Comparison for Different Speaking Rates 

      Sabzi Shahrebabaki, Abdolreza; Imran, Ali Shariq; Olfati, Negar; Svendsen, Torbjørn Karl (Chapter, 2018)
      This paper investigates the effect of speaking rate variation on the task of frame classification. This task is indicative of the performance on phoneme and word recognition and is a first step towards designing voice-controlled ...

    • Machine Learning of Sub-Phonemic Units for Speech Recognition 

      Olfati, Negar (Master thesis, 2015)
      This work is intended to explore the performance of a new set of acoustic model units in speech recognition. The acoustic models were built and evaluated from scratch in several steps: Feature extraction, acoustic detection ...

    • 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 ...