@proceedings{273,
  keywords = {Computing and Processing, Robotics and Control Systems, Signal Processing and Analysis, Dictionaries, Standards, Matrices, Speech recognition, Dynamic programming, Speech, Acoustics},
  author = {Oluwapelumi Giwa and Marelie Davel},
  title = {Bilateral G2P Accuracy: Measuring the effect of variants},
  abstract = { Incorporating pronunciation variants in a dictionary is controversial, as this can be either advantageous or detrimental for a speech recognition system. Grapheme-ophoneme (G2P) accuracy can help guide this decision, but calculating the G2P accuracy of variant-based dictionaries is not fully straightforward. We propose a variant matching technique to measure G2P accuracy in a principled way, when both the reference and hypothesized dictionaries may include variants. We use the new measure to evaluate G2P accuracy and speech recognition performance of systems developed with an existing set of dictionaries, and observe a better correlation between G2P accuracy and speech recognition performance, than when utilising alternative metrics.},
  year = {2017},
  journal = {Pattern Recognition Association of South Africa and Mechatronics International Conference (PRASA-RobMech)},
  chapter = {208-213},
  address = {Bloemfontein, South Africa},
  isbn = { 978-1-5386-2314-5, 978-1-5386-2313-8},
  doi = {10.1109/RoboMech.2017.8261149},
}