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+# Semantic Captions
+
+Copyright © 2024, NVIDIA Corporation, version 1.0
+
+## Goal
+Extend the `usdSemantics` domain with a schema for natural language 
+semantic descriptions of subgraphs of an OpenUSD stage.
+
+## Background
+The proposed semantic labels API provides a mechanism for tagging
+subgraphs with labels using different taxonomies.
+
+```
+def Mesh "orange" (apiSchemas = ["SemanticsLabelsAPI:tags",
+                                 "SemanticsLabelsAPI:state"]) {
+    token[] semantics:labels:tags = ["fruit", "food", "citrus"]
+    token[] semantics:labels:state = ["peeled"]
+}
+```
+
+Labels as discrete tokens makes it easy to construct merged 
+sets of ancestors (to aid `IsLabeled` queries) or generate
+segmentation images. Labels also suggest certain user interfaces and 
+query considerations (ie. drag and drop labels onto prims).
+
+## Proposal
+Some workflows are looking for natural language descriptions of
+subgraphs that can be used to describe a variety of features.
+
+```
+def Xform "dancing_robot" (
+    apiSchemas = ["SemanticsCaptionsAPI:summary",
+                  "SemanticsCaptionsAPI:skills"]
+) {
+    string semantics:captions:summary = "This is a bipedal robot made up of metal that is painted red. The robot was manufactured in 2024."
+    string semantics:captions:skills = "This robot can perform a box step, a grapevine, and the waltz."
+}
+```
+
+Captions are expected to be longer phrases, sentences, or paragraphs.
+A single prim may have multiple named instances of a caption to
+suggest its intent. Multiple instances can also allow for multiple language
+support.
+
+### Time Varying Captions
+Just as labels benefit from being able to describe state changes 
+over time, captions may also be time varying.
+
+```
+def Xform "learning_robot" (
+    apiSchemas = ["SemanticsCaptionsAPI:skills"]
+) {
+    string semantics:captions:skills.timeSamples = {
+        0 : "The robot does not know how to dance",
+        100 : "The robot is learning the box step",
+        150 : "The robot knows the box step"
+    }
+}
+```
+
+### Ancestral captions
+It's expected that captions describe the prim's subgraph. A prim may
+look to ancestors for additional context. API will likely be
+provided to aid in this.
+
+```cpp
+// Find either the instance of the captions API applied directly
+// to prim the nearest hierarchical ancestor of the prim.
+UsdSemanticsCaptionsAPI
+FindNearest(const UsdPrim& prim, const TfToken& instance) const;
+
+// Find all caption instances applied directly to the prim or
+// to ancestors of the prim
+std::vector<UsdSemanticsCaptionsAPI>
+FindHierarchical(const UsdPrim& prim, const TfToken& instance) const;
+```
+
+## Alternatives
+### Use `documentation` metadata
+The documentation metadata would be an alternative. However, it 
+does not allow for multiple instances and may conflict with user
+documentation. For example-- `doc = "This asset is designed for background usage only"`.
+
+### Use `assetInfo` metadata
+Unlike the `documentation` field, an asset info dictionary
+could capture multiple strings in the dictionary. However, they
+cannot vary over time.
+
+### Use `SemanticsLabelsAPI`
+The proposed labeling API could be used to capture captions. 
+There are two reasons to have distinct APIs.
+* An authoring user interface for adding labels should be 
+different than the user interface for adding descriptions. (ie. 
+drop down box vs. text box).
+* Merging ancestor labels into sets to perform membership
+queries has many potential applications (ie. semantically 
+partioned image masks). There is no equivalent workflow for
+captions.
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