Update README.md

README.md

@@ -130,7 +130,7 @@ configs:
 # MuSSeD: Bilingual (English–Korean) Speech-Separation Mixtures
 
 A bilingual **speech-separation** corpus of synthetic multi-speaker mixtures built from
-English ([LibriTTS-R](https://www.openslr.org/141/)) and Korean read-speech sources.
+English ([LibriTTS-R](https://www.openslr.org/141/)) and Korean read-speech sources ([AI-Hub Multi-Speaker Speech Synthesis corpus](https://www.aihub.or.kr/aihubdata/data/view.do?dataSetSn=542)).
 Each mixture concatenates/overlaps **2, 3, or 4** single-speaker utterances, and every
 mixture ships with rich per-speaker JSON metadata (speaker id, gender, language,
 timing, transcription, overlap ratio, source utterance id).
@@ -172,7 +172,7 @@ that matter for separation difficulty — bilingual share and overlap share are
 identical across splits, so validation/test numbers are representative of the training
 distribution.
 
-![Split consistency](./figure/fig3_split_consistency.png)
+![Split consistency](./figure/split_consistency.png)
 
 ### 3. Controlled, full-range overlap
 
@@ -180,7 +180,7 @@ Overlap is not concentrated at one difficulty. Mixtures span the full range from
 clean (no overlap) to fully overlapped, with the harder end growing as speaker count
 increases (2→4 spk), which is the expected and desired behaviour.
 
-![Overlap distribution](./figure/fig4_overlap_distribution.png)
+![Overlap distribution](./figure/overlap_distribution.png)
 
 ### 4. Complete, machine-readable metadata
 
@@ -194,7 +194,7 @@ enabling exact, reproducible analysis of language / gender / overlap / timing.
 The share of bilingual (EN+KO) mixtures grows with speaker count, while EN-only /
 KO-only mixtures remain represented at every count:
 
-![Language composition](./figure/fig5_language_composition.png)
+![Language composition](./figure/language_composition.png)
 
 ---