Update README.md

README.md

@@ -1,3 +1,45 @@
----
-license: cc0-1.0
----
+---
+license: cc0-1.0
+---
+
+# 張悦楷三國演義
+
+Fork from [laubonghaudoi/zoengjyutgaai_saamgwokjinji](https://huggingface.co/datasets/laubonghaudoi/zoengjyutgaai_saamgwokjinji)
+
+We found the original wav files are not splitted correctly, so we asked the author to provide the srt file and un-splitted wav files. We then re-split the wav files and align the srt file to the wav files.
+
+```python
+subtitles = []
+splits = librosa.effects.split(audio) # shape: (682, 2)
+
+!mkdir -p dataset/zoengjyutgaai_saamgwokjinji/wavs
+
+# split audio by srt time
+for i, sub in enumerate(subs):
+    chunk_start = sub.start.to_time()
+    chunk_end = sub.end.to_time()
+    chunk_start = ((chunk_start.minute * 60) + chunk_start.second) * sr
+    chunk_end = ((chunk_end.minute * 60) + chunk_end.second) * sr
+
+    # Find the closest split
+    chunk_start = min(splits, key=lambda x: abs(x[0] - chunk_start))[0]
+    chunk_end = min(splits, key=lambda x: abs(x[1] - chunk_end))[1]
+
+    chunk = audio[chunk_start:chunk_end]
+    wav_file = f"001_{i:03}.wav"
+
+    # resample, since bert-vits2 training only support 44.1k 
+    try:
+        chunk = librosa.resample(chunk, sr, 44100)
+    except:
+        print(f"Error resampling {wav_file}")
+        continue
+
+    subtitles.append({ 'path': wav_file, 'speaker': 'zoengjyutgaai', 'language': 'YUE', 'text': sub.text })
+
+    # export audio
+    sf.write(f"dataset/zoengjyutgaai_saamgwokjinji/wavs/{wav_file}", chunk, 44100, subtype='PCM_16')
+
+df = pd.DataFrame(subtitles)
+df.to_csv("dataset/zoengjyutgaai_saamgwokjinji/001.csv", index=False, sep='|', header=False)
+```