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1
Finding Chunks In Symbolic Time Series
In: http://www.amristar.com.au/~hutch/phd/research1.ps.gz (1999)
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2
The NonI Conversation Simulator
In: http://ciips.ee.uwa.edu.au/~hutch/phd/research9.ps.gz (1998)
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3
Finding Structure via Compression
In: http://ciips.ee.uwa.edu.au/~hutch/phd/conference2.ps.gz (1998)
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4
Language Acquisition and Data Compression
In: http://ciips.ee.uwa.edu.au/~hutch/phd/conference1.ps.gz (1997)
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5
Finding Structure in the Vowel Space
In: http://ciips.ee.uwa.edu.au/Papers/Conference_Papers/1993/04/cp93-04.ps.gz (1993)
Abstract: From the TIMIT database labelled speech waveform segments from 33 speakers were extracted. There were 8 categories of speech data, each representing a vowel sound. In each category were 80 - 130 utterances. The waveform segments were processed by taking a FFT, on 32 msec frames and binning the result into 12 frequency bands. This way each frame will be represented by 12 numbers/values. They become points in IR 12 and each utterance is a short trajectory in IR 12 . The 8 vowel categories become 8 clusters of such trajectories. By projecting the clusters onto the screen of a SUN workstation, it was observed that each vowel cluster appeared to be substantially gaussian. The covariance matrix and the centers were computed. Dimension estimates of each vowel by Principal Components Analysis show that the eight clusters lie close to a plane in the filterbankspace, and that the principal axes of the vowel clusters make a small and consistent angle with respect to this plane. This confirms .
URL: http://ciips.ee.uwa.edu.au/Papers/Conference_Papers/1993/04/cp93-04.ps.gz
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.8258
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6
Affine Transformations of the Speech Space
In: http://ciips.ee.uwa.edu.au/Papers/Conference_Papers//1992/03//cp92-03.ps.gz (1992)
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7
Introducing MegaHAL
In: http://ciips.ee.uwa.edu.au/~hutch/phd/conference3.ps.gz
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