• Acoustic analysis and computerized reconstruction of speech in laryngectomised individuals 

      Sharifzadeh, Hamid; Allen, Jacqui E.; McLoughlin, I.V.; Sarrafzadeh, Hossein; Ardekani, Iman (2016-05)
      In laryngectomised individuals, rehabilitation options include esophageal speech, tracheoesophageal puncture (TEP), and electrolarynx devices enabling patients to communicate. These do not generate natural sounding speech; ...
    • Acoustic features of dysphonic speech vs normal speech in New Zealand English speakers 

      Erfanian Sabaee, Maryam; Sharifzadeh, Hamid (Computing and Information Technology Research and Education New Zealand (CITRENZ), 2021-07)
      This poster presents the acoustic features of distorted speech in three dysphonic New Zealanders compared to three healthy individuals as the control group. There are a total of six subjects in this study. Voice onset time ...
    • Acoustic signal processing systems for intelligent beehive monitoring 

      Ardekani, Iman; Varastehpour, Soheil; Sharifzadeh, Hamid (Acoustical Society of New Zealand, 2022)
      Bees, as pollinators and producers of honey and medicinal products, play a crucial role in human life and environmental sustainability. Emerging Smart Beekeeping technologies utilise various methodologies in apiology, ...
    • Aiding forensic investigations using machine learning 

      Sharifzadeh, Hamid; Varastehpour, Soheil; Francis, X.; Keivanmarz, A.; Fleming, R.; Ardekani, Iman; Newton, A. (2022-11-28)
      Advances in machine learning find rapid adoption in many fields ranging from communications, signal processing, and the automotive industry to healthcare, law, and forensics. In this talk, I briefly focus on a couple of ...
    • Automatic assessment of dysarthric severity level using audio-video cross-modal approach in deep learning 

      Tong, H.; Sharifzadeh, Hamid; McLoughlin, I. (ISCA (International Speech Communication Association), 2020-10)
      Dysarthria is a speech disorder that can significantly impact a person’s daily life, and yet may be amenable to therapy. To automatically detect and classify dysarthria, researchers have proposed various computational ...
    • Bayesian active noise control 

      Ardekani, Iman; Varastehpour, Soheil; Sharifzadeh, Hamid (Acoustical Society of New Zealand, 2022-10)
      Active Noise Control (ANC) is a challenging practical application of adaptive control systems. This paper approaches ANC from the perspective of the Bayesian Inverse Problems theory. The ANC underlying problem is initially ...
    • Bayesian parameter estimation of Euler-Bernoulli beams 

      Ardekani, Iman; Kaipio, J.; Sharifzadeh, Hamid (2018-11)
      This paper develops a statistical signal processing algorithm for parameter estimation of Euler-Bernoulli beams from limited and noisy measurement. The original problem is split into two reduced-order sub-problems coupled ...
    • Bionic voice (pilot study) : natural speech restoration for voice impaired individuals 

      Sharifzadeh, Hamid; Allen, Jacqui E.; Sarrafzadeh, Hossein; Ardekani, Iman (Health Informatics New Zealand, 2016-11)
      The human voice is the most magnificent instrument for communication, capable of expressing deep emotions, conveying oral history through generations, or of starting a war. However, those who suffer from aphonia (no voice) ...
    • Comparative whisper vowel space for Singapore English and British English accents 

      Sharifzadeh, Hamid; Ardekani, Iman; McLoughlin, I.V. (Asia-Pacific Signal and Information Association (APSIPA), 2015-12)
      Whispered speech, as a relatively common form of communications, has received little research effort in spite of its usefulness in everyday vocal communications. Apart from a few notable studies analysing the main whispered ...
    • Efficient FXLMS algorithm with simplified secondary path models. 

      Ardekani, Iman; Sharifzadeh, Hamid; Rehman, Saeed; Abdulla, W. H. (IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015)
      his paper extends the existing work on the root locus analysis of FxLMS algorithm by considering secondary path modeling errors. Rules for sketching FxLMS root locus are set out. An analytic convergence condition is then ...
    • Enhancing customers’ knowledge and decision making using augmented reality 

      Boonrat, W.; Vaidya, V.; Baghaei, Nilufar; Sharifzadeh, Hamid; Ahmed, A.; Casey, John (Asia-Pacific Society for Computers in Education (APSCE), 2020-11)
      Augmented reality has seen massive success in recent years as it provides an opportunity for a seamless and rich user interaction with the real world. Recent studies have shown augmented and virtual reality can play a ...
    • Increasing self-compassion in young people through virtual reality 

      Baghaei, Nilufar; Hach, Sylvia; Khaliq, I.; Stemmet, L.; Krishnan, J.; Naslund, J.; Liang, H.L.; Sharifzadeh, Hamid (2019-10)
      As part of our proposal, we aim to:  provide increased practice/exposure and target a younger audience  increase the chance of generalisation to everyday life  employ better VR visualisation, e.g. assigning more ...
    • Maximum a posteriori adjustment of adaptive transversal filters in active noise control 

      Ardekani, Iman; Zhang, X.; Sharifzadeh, Hamid; Kaipio, J. (2017-12)
      This paper develops a novel approach to adaptive active noise control based on the theory of Bayesian estimation. Control system parameters are considered as statistical variables and a formulation for the joint probability ...
    • A novel adaptive active noise control algorithm based on Tikhonov regularisation 

      Ardekani, Iman; Sakhaee, N.; Sharifzadeh, Hamid; Barmada, Bashar; Lovell, G. (2018-11)
      This paper proposes a novel adaptive active noise control algorithm based on Tikhonov regularization theory. A regularized cost function consisting of the weighted sum of the most recent samples of the residual noise and ...
    • Phonated speech reconstruction using twin mapping models 

      Sharifzadeh, Hamid; HajiRassouliha, Amir; McLoughlin, I.V.; Ardekani, Iman; Allen, Jacqueline E. (IEEE Communications Society, 2015-12)
      Computational speech reconstruction algorithms have the ultimate aim of returning natural sounding speech to aphonic and dysphonic individuals. These algorithms can also be used by unimpaired speakers for communicating ...
    • Vein pattern visualization through multiple mapping models and local parameter estimation for forensic investigation 

      Sharifzadeh, Hamid; Zhang, Hengyi; Kong, Adams Wai-Kin (International Conference on Pattern Recognition (ICPR), 2014)
      Forensic investigation methods based on some human traits, including fingerprint, face, and palmprint, have been developed significantly, but some major aspects of particular crimes such as child pornography still lack of ...
    • Visualising vein pattern using deep learning for forensic investigation 

      Varastehpour, Soheil; Sharifzadeh, Hamid (2021-12)
      Child sexual abuse is a severe global problem that has gained public attention in recent years. Due to the popularity of digital cameras, many perpetrators take images of their sexual activities. Even though most common ...