This page provides information on Fine-Tracker: a computational model of human word recognition, built using techniques from the field of automatic speech recognition (ASR), which is able to capture and use fine-grained acoustic-phonetic variation during speech recognition.
Like its cousin SpeM (Scharenborg et al., 2005), Fine-Tracker can take realistic representations of the speech signal as its input and subsequently perform a word search based on the theory of human word recognition as explained in Norris (1994). Fine-Tracker takes multi-tier vector representations of the speech signal, for instance created by an artificial neural network, as its input. The output of Fine-Tracker consists of an Nbest list of the most likely word sequences.
Download the Fine-Tracker (ftracker) software package
- 04/11/2009: A new version of Fine-Tracker is available. Fine-Tracker Version 1.2 is able to use unigram and bigram language models. This package also includes a tool to create your own language models for use with Fine-Tracker.
- Version 1.0
Details about Fine-Tracker’s implementation, its objective, background, and initial experiments are described in the following papers/abstracts:
- Scharenborg, O. (2010). Modeling the use of durational information in human spoken-word recognition. Journal of the Acoustical Society of America, 127 (6), 3758-3770. This article may be found at http://link.aip.org/link/?JAS/127/3758 or here. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. Copyright (2010) Acoustical Society of America. Download
- Scharenborg, O. (2009). Using durational cues in a computational model of spoken-word recognition. Proceedings of Interspeech, Brighton, UK, September 2009, pp. 1675-1678. Download
- Scharenborg, O. (2008). Modelling fine-phonetic detail in a computational model of word recognition. Proceedings of Interspeech, Brisbane, Australia, September 2008, pp. 1473-1476. Download
- Scharenborg, O. (2008). Fine-phonetic variation in a computational model of word recognition. Poster presentation at Acoust. Soc. Am. mtg, Paris, July 2008. Download
ftracker 1.0, 1.2 Copyright (C) 2008, 2009 Radboud University Nijmegen
This project was made possible by a Veni-grant from NWO (the Netherlands Organisation for Scientific Research).
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