The utterance structure is represented internally as a heterogeneous relation graph (HRG), which consists of a set of relations, where each relation contains some items (the items need not be unique to a relation). The relations represent structures such as words, syllables, phonemes or even duration targets and the items are the content of these structures.
Figure 4 shows an example representation of an utterance structure, for the text input “twenty fifth”, using a HRG with four relations and their items. The relations are:
- Word - where the items are the words in the utterance.
- Syllable - the items are the syllables in the words.
- Segment - the items represent phones in the words.
- SylStruct - a relation that connects the Word, Syllable and Segment relations.
Note that for brevity the phones of the word “fifth” have been omitted. The figure also shows the item’s features, for example, the Word relation’s items have as a “name” feature the word it was derived from, whereas the Syllable relation’s items have a “stress” feature (0 or 1). The number of features are conceptually unlimited, the only restriction being that the feature names are unique in a specific item.
The following sections discuss abstract HRG functions that are implemented in Speect.
The traversal of the graph is done with four basic functions, previous, next, parent and daughter:
Previous and Next
In the Word, Syllable and Segment relations we can see that all items are connected, i.e. all items have a previous and a next item (except of course the head and tail items), while this is not the case for the SylStruct relation. The SylStruct relation’s items have breaks in between certain items.
Parent and Daughter
The SylStruct relation’s items have parent and daughter nodes, which the other three relations do not have. Each item has one parent node, for example, the /eh/ phone’s parent is the first Syllable relation item. An item may have multiple daughter nodes, the first word item (“twenty”) has 2 daughter nodes, which in turn have their own daughter nodes.
The parent function will traverse to the left to find the leftmost connected item, and return it’s parent item.
Each item is a unique node in the graph, but items may share their contents or features. In other words, although all items are unique, conceptually items that share their contents can be viewed as the same item. For example in figure 4, one can see that all the items in the Word relation share their contents with the top level of items in the SylStruct relation.
This concept enables us to switch relations while traversing:
As relation
Lets start traversing the Segment relation from left to right. None of the item’s have a parent item, but we can switch to the SylStruct relation with the as relation function, from where we can find parent items in the form of the syl items.
In relation
While still traversing the Segment relation, we can query each item if it shares it’s content with an item in another relation (in relation). While all the Segment relation items do share their content with items in the SylStruct relation, none of them share content with any items in the Word relation.
The HRG structure can be extended as follows:
Append
Items can be appended to other items, or relations.
Pre-pend
Items can be pre-pended to other items, or relations.
Add daughter
Items can be added as daughter items of other items.
HRG traversal can also be accomplished by item paths. Let’s say for argument’s sake that we have as a starting point the last phone of a word (“twenty”) as it is in the Segment relation (/iy/ item). Now we want to traverse to the first Syllable item of the next word. We would have to call the following sequence of functions:
- as relation SylStruct
- parent
- parent
- next
- daughter
- as relation Syllable
The above sequence requires a lot of coding, which can be replaced with item paths. Paths consists of period (”.”) separated tokens that represent a traversal or content switch function. For example, the following token string will execute exactly the same sequence of functions:
R:SylStruct.parent.parent.n.daughter.R:Syllable
The possible tokens are:
Token | Meaning |
---|---|
p | previous item |
n | next item |
daughter | first daughter item |
daughtern | last daughter item |
parent | parent item |
R:relname | item as it is in the given relation relname |
We can also extract a feature of the path item by adding a feature processor name to the end of the path. Let’s say for example that we have a feature processor, named “syltone”, that can calculate a syllable item’s tone. The path can then be:
R:SylStruct.parent.parent.n.daughter.R:Syllable.syltone
The same can also be done for any named feature of an item, for example:
R:SylStruct.parent.parent.n.name
will return “fifth”, as that is the name of the second Word relation item in figure 4.