Summary of the paper

Title LIPS: A Tool for Predicting the Lexical Isolation Point of a Word
Authors Andrew Thwaites, Jeroen Geertzen, William D. Marslen-Wilson and Paula Buttery
Abstract We present LIPS (Lexical Isolation Point Software), a tool for accurate lexical isolation point (IP) prediction in recordings of speech. The IP is the point in time in which a word is correctly recognised given the acoustic evidence available to the hearer. The ability to accurately determine lexical IPs is of importance to work in the field of cognitive processing, since it enables the evaluation of competing models of word recognition. IPs are also of importance in the field of neurolinguistics, where the analyses of high-temporal-resolution neuroimaging data require a precise time alignment of the observed brain activity with the linguistic input. LIPS provides an attractive alternative to costly multi-participant perception experiments by automatically computing IPs for arbitrary words. On a test set of words, the LIPS system predicts IPs with a mean difference from the actual IP of within 1ms. The difference from the predicted and actual IP approximate to a normal distribution with a standard deviation of around 80ms (depending on the model used).
Topics Tools, systems, applications, Cognitive methods, Language modelling
Full paper LIPS: A Tool for Predicting the Lexical Isolation Point of a Word
Slides -
Bibtex @InProceedings{THWAITES10.326,
  author = {Andrew Thwaites and Jeroen Geertzen and William D. Marslen-Wilson and Paula Buttery},
  title = {LIPS: A Tool for Predicting the Lexical Isolation Point of a Word},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
 }
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