Update README.md

README.md

@@ -57,21 +57,13 @@ Three strategies are provided per backbone:
 ---
 
 ## Uses
-
-### Direct Use
 - Research/prototyping for **pronunciation scoring** and **representation analysis** (e.g., PCA on hidden states).
 - Feature extraction for downstream APA tasks.
-
-### Downstream Use
-- Integrate APA scores into CALL and assessment tools.  
-- Use **CTC** variants in ASR-aligned pipelines; use **General/Freeze** for regression of APA scores.
-
 ---
 
 ## Bias, Risks, and Limitations
 - Trained/evaluated on **Speechocean762** (read English by L2 speakers). Generalization to other languages/speaking styles is not guaranteed.  
 - APA relies on subjective human scores; apply domain calibration and monitor subgroup performance.
-
 **Recommendation:** Validate on in-domain data; report uncertainty and subgroup metrics.
 
 ---
@@ -178,37 +170,6 @@ python train/ctc.py \
 - **Test set:** Speechocean762 (held-out split prepared by `preprocess_dataset.py`)
 - **Factors:** Backbone (Wav2Vec2 / HuBERT / WavLM) × strategy (CTC / General / Freeze)
 - **Metric:** `pearsonr` (Pearson correlation coefficient, PCC) for Accuracy, Fluency, Prosody, and Total.
-
-### Results (PCC highlights)
-- **Best Total PCC (paper):** ~**0.745** (HuBERT xlarge ls960-ft; strong results for CTC/Freeze variants).  
-- Wav2Vec2-large/960h show strong **Fluency**/**Total** under General.
-- Full table is in the paper and GitHub README.
-
-#### Summary
-- **CTC** benefits ASR-aligned objectives.  
-- **General/Freeze** directly regress APA scores and support representation analysis (e.g., PCA).
-
----
-
-## Model Examination (Intrinsic Analysis)
-PCA on hidden representations reveals distinct geometries:
-- **Wav2Vec2:** conical (score continuity)  
-- **HuBERT:** V-shape (two-axis decision)  
-- **WavLM:** S-shape (diverse scoring factors)
-
----
-
-## Technical Specifications
-
-### Architecture & Objective
-- Backbones: Wav2Vec2.0 / HuBERT / WavLM  
-- Objectives:
-  - **CTC:** ASR-style CTC head  
-  - **General/Freeze:** regression head predicting 4 APA scores
-
-### Compute Infrastructure
-- See saved configs/logs per run (`trainer_state.json`, `training_args.bin`, `args.json`).
-
 ---
 
 ## Citation