Update README.md

README.md

@@ -22,9 +22,11 @@ pretty_name: SmoothConv
   <a href="https://github.com/qualialabsAI/SmoothConv-DuplexConv"><img src="https://img.shields.io/badge/GitHub-Repo-green" alt="GitHub"></a>
 </p>
 
+**Companion dataset:** [**DuplexConv**](https://huggingface.co/datasets/qualialabsAI/DuplexConv) on HuggingFace (2,000 hours, LLM-assisted annotation). SmoothConv (100 hours) and DuplexConv are drawn from the same or closely related sources. Use SmoothConv for fine-grained benchmarking and DuplexConv for large-scale training.
+
 ## Dataset Summary
 
-SmoothConv provides **~100 hours** of real-world, unscripted **multi-party Chinese dialogue** recorded in **multi-channel** settings across **Tutoring** and **Social Chat** scenarios. Conversations capture natural full-duplex interaction phenomena—including overlapping speech, backchannels, interruptions, and pauses.
+SmoothConv provides **100 hours** of real-world, unscripted **multi-speaker Chinese dialogue** recorded in **multi-channel** settings across **Tutoring** and **Social Chat** scenarios. Conversations capture natural full-duplex interaction phenomena, including overlapping speech, backchannels, interruptions, and pauses.
 
 Human annotators provide fine-grained labels suitable for benchmarking and supervised training on turn-taking, overlap detection, and spoken dialogue understanding.
 
@@ -126,15 +128,6 @@ for seg in anno["instances"]:
     print(seg["channelIndex"], seg["start"], seg["end"], seg["text"])
 ```
 
-## Relation to DuplexConv
-
-SmoothConv and [DuplexConv](https://huggingface.co/datasets/qualialabsAI/DuplexConv) are complementary datasets drawn from the same or closely related conversation sources:
-
-- **SmoothConv** (~100h): expert human annotations for precision and benchmarking
-- **DuplexConv** (~2,000h): LLM-assisted annotations for large-scale coverage
-
-A turn-state evaluation subset derived from SmoothConv is also available as the [FastTurn Test Set](https://huggingface.co/datasets/ASLP-lab/FastTurn-Testset).
-
 ## Ethics Statement
 
 - **Informed consent.** Conversations were recorded with the knowledge and consent of participants. Personal identifiers have been removed or anonymized prior to release.