Now showing items 1-5 of 5

  • An ultra low-power hardware accelerator for automatic speech recognition 

    Yazdani Aminabadi, Reza; Segura Salvador, Albert; Arnau Montañés, José María; González Colás, Antonio María (IEEE Press, 2016)
    Conference report
    Open Access
    Automatic Speech Recognition (ASR) is becoming increasingly ubiquitous, especially in the mobile segment. Fast and accurate ASR comes at a high energy cost which is not affordable for the tiny power budget of mobile devices. ...
  • Low-power automatic speech recognition through a mobile GPU and a Viterbi accelerator 

    Yazdani Aminabadi, Reza; Segura Salvador, Albert; Arnau Montañés, José María; González Colás, Antonio María (2017-04-12)
    Article
    Open Access
    Automatic speech recognition (ASR) has become a core technology for mobile devices. Delivering real-time and accurate ASR has a huge computational cost, which is challenging to achieve in tightly energy-constrained platforms ...
  • The dark side of DNN pruning 

    Yazdani Aminabadi, Reza; Arnau Montañés, José María; González Colás, Antonio María; Riera Villanueva, Marc (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Conference report
    Restricted access - publisher's policy
    DNN pruning has been recently proposed as an effective technique to improve the energy-efficiency of DNN-based solutions. It is claimed that by removing unimportant or redundant connections, the pruned DNN delivers higher ...
  • Ultra low-power, high-performance accelerator for speech recognition 

    Yazdani Aminabadi, Reza (Universitat Politècnica de Catalunya, 2019-07-25)
    Doctoral thesis
    Open Access
    Automatic Speech Recognition (ASR) is undoubtedly one of the most important and interesting applications in the cutting-edge era of Deep-learning deployment, especially in the mobile segment. Fast and accurate ASR comes ...
  • UNFOLD: a memory-efficient speech recognizer using on-the-fly WFST composition 

    Yazdani Aminabadi, Reza; Arnau Montañés, José María; González Colás, Antonio María (Association for Computing Machinery (ACM), 2017)
    Conference report
    Restricted access - publisher's policy
    Accurate, real-time Automatic Speech Recognition (ASR) requires huge memory storage and computational power. The main bottleneck in state-of-the-art ASR systems is the Viterbi search on a Weighted Finite State Transducer ...