Update README.md

README.md

@@ -17,7 +17,7 @@ X-Codec2 is a neural audio codec designed to improve speech synthesis and genera
 
 About its architecture:
 - **Unified Semantic-Acoustic Tokenization**: X-Codec2 fuses outputs from a semantic encoder (e.g., Wav2Vec2-BERT) and an acoustic encoder into a single embedding, capturing both high-level meaning (e.g., text content, emotion) and low-level audio details (e.g., timbre).
-- **Single-Stage Vector Quantization (VQ)**: Unlike the multi-layer residual VQ in most approaches (e.g., XCodec, DAC, Encodec, Mimi), X-Codec2 uses a single-layer of Feature Scalar Quantization (FSQ) for stability and compatibility with causal, autoregressive LLMs.
+- **Single-Stage Feature Scalar Quantization (FSQ)**: Unlike the multi-layer residual VQ in most approaches (e.g., DAC, Encodec, Mimi), X-Codec2 uses a single-layer of Feature Scalar Quantization (FSQ) for stability and compatibility with causal, autoregressive LLMs.
 - **Transformer-Friendly Design**: The 1D token structure of X-Codec2 naturally aligns with the autoregressive modeling in LLMs like LLaMA, improving training efficiency and downstream compatibility.
 
 This checkpoint was contributed by [Eric Bezzam](https://huggingface.co/bezzam) and [Steven Zheng](https://huggingface.co/Steveeeeeeen).