publications:
- title: "Manifold Learning-Based Feature Transformation for Phone Classification"
  author:
  - name: "Andrew Errity"
    link: "http://ccta.iadt.ie/ccta/staffcv.php?staffid=22"
  - name: "John McKenna"
    link: "https://researchr.org/alias/john-mckenna"
  - name: "Barry Kirkpatrick"
    link: "https://researchr.org/alias/barry-kirkpatrick"
  year: "2007"
  doi: "http://dx.doi.org/10.1007/978-3-540-77347-4_10"
  links:
    doi: "http://dx.doi.org/10.1007/978-3-540-77347-4_10"
  tags:
  - "rule-based"
  - "classification"
  - "transformation"
  researchr: "https://researchr.org/publication/ErrityMK07"
  cites: 0
  citedby: 0
  pages: "132-141"
  booktitle: "Advances in Nonlinear Speech Processing, International Conference on Non-Linear Speech Processing, NOLISP 2007, Paris, France, May 22-25, 2007, Revised Selected Papers"
  editor:
  - name: "Mohamed Chetouani"
    link: "https://researchr.org/alias/mohamed-chetouani"
  - name: "Amir Hussain"
    link: "https://researchr.org/alias/amir-hussain"
  - name: "Bruno Gas"
    link: "https://researchr.org/alias/bruno-gas"
  - name: "Maurice Milgram"
    link: "https://researchr.org/alias/maurice-milgram"
  - name: "Jean-Luc Zarader"
    link: "https://researchr.org/alias/jean-luc-zarader"
  volume: "4885"
  series: "Lecture Notes in Computer Science"
  publisher: "Springer"
  isbn: "978-3-540-77346-7"
  kind: "inproceedings"
  key: "ErrityMK07"
- title: "Unscented Kalman Filtering of Line Spectral Frequencies"
  author:
  - name: "Andrew Errity"
    link: "http://ccta.iadt.ie/ccta/staffcv.php?staffid=22"
  - name: "John McKenna"
    link: "http://"
  - name: "S. Isard"
    link: "http://"
  year: "2004"
  month: "October"
  abstract: "We propose a new method for estimating Line Spectral Frequency (LSF) trajectories that uses unscented {K}alman filtering (UKF). This method is based upon an iterative Expectation Maximisation (EM) approach in which LSF estimates are generated during a forward pass and then smoothed during a backward pass. The EM approach also provides re-estimated {K}alman filter parameters for further forward-backward passes that improve estimation. This approach exploits the non-independence of neighbouring spectra. We estimate LSFs as they have good interpolation and quantization properties. This allows us to estimate LSF trajectories that are guaranteed to result in stable filters. We analyse noisy synthetic speech using this technique. The results compare favourably with other methods."
  links:
    "url": "http://www.isca-speech.org/archive/archive_papers/interspeech_2004/i04_2697.pdf"
  tags:
  - "rule-based"
  - "systematic-approach"
  researchr: "https://researchr.org/publication/Errity2004"
  cites: 0
  citedby: 0
  booktitle: "Proc. of the Int. Conf. on Spoken Language Processing (Interspeech 2004 - ICSLP)"
  address: "Jeju, Korea"
  kind: "inproceedings"
  key: "Errity2004"