Update README.md

README.md

@@ -36,4 +36,58 @@ tags:
 - ASR
 size_categories:
 - n<1K
----
+---
+
+
+
+# Expresso Conversational EN Nano-Codec Dataset
+
+This dataset is built upon the [Expresso conversational dataset](https://huggingface.co/datasets/nytopop/expresso-conversational) and re-encoded using NVIDIA’s [NeMo Audio Codec](https://huggingface.co/nvidia/nemo-nano-codec-22khz-0.6kbps-12.5fps) into **nano audio tokens**.  
+
+It is designed for **fine-tuning multimodal LLMs** and **speech systems (TTS/ASR)** that rely on codec-based audio token representations.
+
+---
+
+## Dataset Structure
+
+- **text**: transcription of the utterance.  
+- **speaker**: speaker identifier (string).  
+- **nano_layer_1 … nano_layer_4**: tokenized audio representations from the NVIDIA NeMo Nano Codec (4-layer quantization).  
+- **encoded_len**: sequence length of encoded audio tokens.  
+
+---
+
+## Use Cases
+
+- **Fine-tuning TTS** models with codec-based speech tokens.  
+- **Training ASR** systems that operate on discrete audio units.  
+- **Multimodal LLM adaptation**, where text and audio tokens are combined.  
+
+This format makes it easier to build compact and efficient speech-enabled LLMs.
+
+---
+
+## Example
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("nineninesix/expresso-conversational-en-nano-codec-dataset", split="train")
+
+print(ds[0]["text"])
+# "Ribbit Nice to meet you, Stephen."
+
+print(ds[0]["nano_layer_1"][:10])
+# [1633, 2685, 3825, 1392, ...]
+````
+
+---
+
+## Credits
+
+* Original text data: [Expresso dataset](https://huggingface.co/datasets/nytopop/expresso-conversational).
+* Audio codec tokenization: [NVIDIA NeMo Codec](https://huggingface.co/nvidia/nemo-nano-codec-22khz-0.6kbps-12.5fps).
+
+
+
+