Time map domains
In the relative time domain, we are interested in the temporal relations which exist between features in an autosegmental representation. In the absolute time domain, on the other hand we are interested in token utterances with actual temporal annotations. What is required in speech recognition, for example, is a mapping from the absolute time annotations to a relative time domain in which the actual time is no longer required. Likewise, speech synthesis requires a mapping from the relative time domain to the absolute time domain since here also temporal annotations or at least average durations are required.
In the rest of this section we will concentrate on the the relative time domain. We will return to the absolute time domain in the section on linguistic word recognition. In order to incorporate temporal relations into our description of syllables we must define the symbols for precedence (<) and overlap (). We can incorporate this information into our representation by invoking an FST in our general Syllable definition:
Syllable: ... <rel-time> == Relations:<<>>.The first two equations of the Relations transducer are just a version of the IDEM transducer discussed in the section on finite state transducers, above (but where variable $G ranges over features and square brackets). The next three equations simply delete any empty feature bundles ([ ]). And the final pair of equations introduce the temporal relations into the representation (where variables $F1 and $F2 range over features).
Relations: <> == Null <$G> == $G <> <[ ]> == <> <[ [ ]> == <[> <] [ ]> == <]> <] [> == ] '<' <[> <$F1 $F2> == $F1 o <$F2>.
We can now infer the following feature information for the example syllable /dOk/:
S_dOk: <rel-time structure featural> = [ [ [voiced] o [plosive] o [alveolar] ] ] < [ [ [voiced] o [vowellike] o [back] o [mid] o [round] o [lax] ] ] < [ [ [voiceless] o [plosive] o [velar] ] ]
Show the (transduced) feature information for S_tee, S_E6 and the ten segment syllable node that you constructed for an earlier exercise.
¡¹ Multilinear descriptions ¡¹ Feature representations ¡¹ Nonsegmental phonology