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Re: Soft/loud grouping patterns

Dear Al and List
>> >>According to Handel, Fraisse explained this in his 1956 book as an
>> >>effect of grouping:
>> >>1. the louder events group with following quieter events .... [big snip]
>> >>Is there a general underlying principle operating here? Why would
>> >>louder events group with following quieter events rather than preceding
>> >>quieter events?
>Perhaps a bias in favor of grouping sounds in the order "strong-weak"
>might be useful in everyday auditory perception.  First it is worth noting
>that the onset of a sound is usually its most intense part (especially in
>the case of impacts, plucked strings, and released-stop syllables such as
>/da/ in speech) with weaker continuing vibrations and echoes following. A
>bias towards grouping in the order "strong-weak" would tend to ensure that
>the onset of a sound (which may be somewhat different from the rest of the
>sound because of onset transients and spectral spread) would group with
>the remaining parts (including echoes) of the SAME sound rather than with
>the tail end of the previous sound.

                                                                                        I                                                       I
                                                                                        I                       -Rhyme-
                                                                                        I                               I                               |
                                                                                        On                      Nu                       Coda

Surely in the case of syllables the most intense part is usually the syllable
nucleus (Nu)? The nucleus, usually a vowel, is also considerably longer. Thus
syllable onsets (on) generally form a "weak-strong" relationship with the
nucleus. This is an example of 'backward' grouping, certainly in the case of
isolated syllables. Again I would argue that a sensory memory model provides
a good account of this (e.g. see Todd, N.P.McAngus and Brown, G.J. (1996)
Visualization of rhythm, time and metre. Artificial Intelligence Review   10,
253-273. )