Update README.md

README.md

@@ -146,7 +146,9 @@ timing, transcription, overlap ratio, source utterance id).
 
 ## Reliability & Verification
 
-This dataset is designed for **trustworthy evaluation**.
+MuSSeD is built for leakage-free, representative evaluation: splits are speaker-disjoint, 
+dev/test mirror the train distribution, overlap spans the full difficulty range, and every mixture ships with complete 
+per-speaker ground truth — each property is summarized below.
 
 ### 1. Speaker-disjoint splits
 
@@ -160,9 +162,9 @@ Speaker identity is parsed directly from the mixture filename (the token after e
 | test  | 88  |
 | **total** | **514** (322 EN + 192 KO) |
 
-### 2. Representative splits (dev/test track train)
+### 2. Representative splits
 
-The dev and test splits follow the **same distributions** as train for the properties
+The dev and test splits follow the same distributions as train for the properties
 that matter for separation difficulty — bilingual share and overlap share are nearly
 identical across splits, so validation/test numbers are representative of the training
 distribution.
@@ -177,7 +179,7 @@ increases (2-4 spk), which is the expected and desired behaviour.
 
 <img src="./figure/overlap_distribution.png" width="70%">
 
-### 4. Complete, machine-readable metadata
+### 4. Metadata
 
 Every mixture has a paired JSON with per-speaker ground truth,
 enabling exact, reproducible analysis of language / gender / overlap / timing.
@@ -186,8 +188,8 @@ enabling exact, reproducible analysis of language / gender / overlap / timing.
 
 ## Composition
 
-The share of bilingual (EN+KO) mixtures grows with speaker count, while EN-only /
-KO-only mixtures remain represented at every count:
+The share of bilingual mixtures grows with speaker count, while English-only /
+Korean-only mixtures remain represented at every count:
 
 <img src="./figure/language_composition.png" width="65%">
 
@@ -214,7 +216,7 @@ utterance ids, each of the form `EN_<spk>_...` or `KO_<spk>_...` — e.g. a 4spk
 `KO_5801_..._KO_5487_..._KO_5495_..._KO_5396_....wav` encodes speakers KO_5801,
 KO_5487, KO_5495, KO_5396.
 
-### JSON schema (per mixture)
+### JSON
 
 ```json
 {
@@ -246,7 +248,7 @@ KO_5487, KO_5495, KO_5396.
 from datasets import load_dataset
 import json
 
-# config = "2spk" | "3spk" | "4spk"  (Kaldi-style file lists live in the "scp" config)
+# config = "2spk" | "3spk" | "4spk"
 ds = load_dataset("syshim/MuSSeD-EnKo", "2spk", split="test")
 
 ex      = ds[0]
@@ -262,7 +264,7 @@ langs   = [s["language"] for s in meta["speakers"]]
 
 ## License
 
-This dataset is derived from multiple sources with **different licenses**:
+This dataset is derived from multiple sources:
 
 - **English audio** originates from **LibriTTS-R** (CC BY 4.0).
 - **Korean audio** originates from a Multi-speaker Speech Synthesis Data by National Information Society Agency (NIA)