🚀 go-pugleaf

Using digitised phones to generate Amiga's speech would make things worse,
not better. Guaranteed. 

However, there may be another way to skin this cat. 

In a recent tech report, Terry Sejnowski at JHU described an experiment with 
an artificial 'neural' network which learns to pronounce English words. 
The paper is :

@techreport     ( SEJNOWSKI86A,
key     =       "Sejnowski" ,
author  =       "Terrence Sejnowski and Charles Rosenberg" ,
title   =       "NETtalk: A Parallel Network that Learns to Read
Aloud" ,
institution=    "Johns Hopkins University" ,
number  =       "JHU-EECS-86-01" ,
year    =       "1986" ,
keywords=       "applications, NETtalk, speech generation" ,
annote  =       "Backprop was used to teach a 3-layer network how
to pronounce textual input. Input layer = 7-character window of local
chars; output layer = distributed phoneme features. Impressive
performance; improved by more hidden units, an extra hidden layer,
and/or using pure dictionary words (rather than inconsistent real-life
data). Damage-resistant, since distributed. [jmt/***]" ,
bibdate =       "Wed Mar  2 11:10:30 1988" ,
)

- The network takes a sliding window in the text and outputs a description of 
the required phone (voiced/unvoiced  dental/paletal.... etc etc) required to utter it.

From my experience in working with connectionist speech recognition, I have little doubt that the network could be extended to learn to produce the actual waveform (or LPC coefficients or whatever) for the speech. Perhaps CA would like to offer me a summer job trying :-). 

In any case, if C-A is thinking of improving the speech on the amiga, it would 
certainly be worth their while to get a copy of this TR.

Michael

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Michael.Witbrock@cs.cmu.edu mjw@cs.cmu.edu                          \
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