Blar i Institutt for elektroniske systemer på forfatter "Imran, Ali Shariq"

Viser treff 1-8 av 8

    • 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 ...

    • Automatic annotation of lecture videos for multimedia driven pedagogical platforms 

      Imran, Ali Shariq; Alaya Cheikh, Faouzi; Kowalski, Stewart James (Peer reviewed; Journal article, 2016)
      Today’s eLearning websites are heavily loaded with multimedia contents, which are often unstructured, unedited, unsynchronized, and lack inter-links among different multimedia components. Hyperlinking different media ...

    • MOOC dropout prediction using machine learning techniques: Review and research challenges 

      Dalipi, Fisnik; Imran, Ali Shariq; Kastrati, Zenun (Chapter, 2018)
      MOOC represents an ultimate way to deliver educational content in higher education settings by providing high-quality educational material to the students throughout the world. Considering the differences between traditional ...

    • Noise Robustness in Small-Vocabulary Speech Recognition 

      Haflan, Vetle (Master thesis, 2019)
      Denne masteroppgaven omhandler små-vokabular talegjenkjenning, og mer spesifikt støyrobusthet i systemer designet for dette formål. Tradisjonelle og moderne gjenkjenningssystemer har blitt trent på relativt store mengder ...

    • Performance analysis of machine learning classifiers on improved concept vector space models 

      Kastrati, Zenun; Imran, Ali Shariq (Journal article; Peer reviewed, 2019)
      This paper provides a comprehensive performance analysis of parametric and non-parametric machine learning classifiers including a deep feed-forward multi-layer perceptron (MLP) network on two variants of improved Concept ...

    • Sub-Nyquist sampling and detection in Costas coded pulse compression radars 

      Hanif, Adnan; Mansoor, Atif Bin; Imran, Ali Shariq (Peer reviewed; Journal article, 2016)
      Modern pulse compression radar involves digital signal processing of high bandwidth pulses modulated with different coding schemes. One of the limiting factors in the radar’s design to achieve desired target range and ...

    • 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 ...