Update README.md

README.md

@@ -41,7 +41,6 @@ Unlike many NLP corpora that normalise or correct non-standard language, this da
 | Total labelled instances | 11,410 |
 | Intent categories | 23 |
 | Annotation framework | INCA Communicative Coding System |
-| Source corpus | CHILDES |
 | Language | English |
 | Task | Intent Classification |
 
@@ -200,4 +199,44 @@ Conversely:
 
 - **Agreement or Acknowledgement**
 
-showed **low lexical diversity**, as these responses often rely on short, formulaic expressions such as:
+showed **low lexical diversity**, as these responses often rely on short, formulaic expressions such as: Yes, Okay, Yeah
+
+
+---
+
+# Developmental Linguistic Features
+
+The dataset preserves several characteristics typical of **early child language**.
+
+| Feature | Percentage |
+|------|------|
+| Telegraphic speech | 19.67% |
+| Shortened forms | 8.32% |
+| Missing function words | 9.52% |
+
+Telegraphic speech refers to utterances dominated by **content words** while omitting grammatical elements.
+
+Examples: Want Juice, Doggy Running, Baby Sleep
+
+
+Preserving these patterns allows models trained on this dataset to better interpret **non-standard developmental speech**.
+
+---
+
+# Intended Use
+
+The dataset is intended for research in:
+
+- Child-centred NLP
+- Intent classification
+- Developmental linguistics
+- Child-robot interaction
+- Conversational AI for children
+- Human–AI interaction in early childhood environments
+
+---
+
+
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+
+