Update README.md

README.md

@@ -7,6 +7,8 @@ configs:
     data_files:
       - split: only_gender_reliable
         path: metadata.csv
+      - split: emotion_gender_reliable
+        path: emotion_metadata.csv
 ---
 # Introduction
 ## Motivation
@@ -21,15 +23,21 @@ We have completed initial collection and filtering of existing datasets, with pl
 
 ## Filter for Usable
 
-<!-- 长度问题，将双声道音频统一为单通道 -->
+To ensure the quality and consistency of the audio data, we applied the following preprocessing steps:
+
+Duration Filtering: Audio clips shorter than 5 seconds or longer than 15 seconds were excluded to maintain a consistent length range suitable for analysis.
+
+Resampling: All audio files were resampled to a 16 kHz sampling rate, which is commonly used in speech processing tasks to balance quality and computational efficiency.
+
+Channel Conversion: Stereo audio files were converted to mono by averaging the left and right channels. This step ensures uniformity across the dataset and simplifies subsequent processing.
 
 ## Filter for Transcription
 
-<!-- 使用什么模型，多大wer是能接受的，为啥选这个 -->
+We used Whisper-Large-v3-turbo to evaluate transcription quality, retaining only samples with a Word Error Rate (WER) below 0.1. This model was chosen for its strong performance and fast inference, making it suitable for large-scale filtering. The WER threshold ensures high-quality transcriptions and reduces noise for downstream tasks.
 
 ## Filter for Gender
-<!-- 人工检验，四位参与人员，四位人员都意见一致则保留，反之舍去 -->
+Manual verification was conducted by four annotators. Only samples with unanimous agreement among all four were retained; others were discarded.
 ## Filter for Emotion
-<!-- 人工检验，四位参与人员，四位人员都意见一致则保留，反之舍去 -->
+For both gender and emotion filtering, samples were manually reviewed by four annotators. Only those with unanimous agreement were kept.