update README and cleanup dirt

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README.md

@@ -1,31 +1,5 @@
 ---
 dataset_info:
-- config_name: 30s
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  - name: text
-    dtype: string
-  - name: id
-    dtype: string
-  - name: condition_on_prev
-    dtype: string
-  - name: duration
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 3194102757.33
-    num_examples: 3659
-  - name: validation
-    num_bytes: 410704018.0
-    num_examples: 462
-  - name: test
-    num_bytes: 355118867.0
-    num_examples: 398
-  download_size: 3379797146
-  dataset_size: 3959925642.33
 - config_name: clean
   features:
   - name: audio
@@ -50,30 +24,6 @@ dataset_info:
     num_examples: 3813
   download_size: 3311132741
   dataset_size: 3316440190.0
-- config_name: clean_extra
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  - name: text
-    dtype: string
-  - name: id
-    dtype: string
-  - name: session_id
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 343502934.86
-    num_examples: 5990
-  - name: validation
-    num_bytes: 21223349.0
-    num_examples: 397
-  - name: test
-    num_bytes: 17421320.0
-    num_examples: 282
-  download_size: 398165352
-  dataset_size: 382147603.86
 - config_name: default
   features:
   - name: audio
@@ -93,14 +43,6 @@ dataset_info:
   download_size: 3346820592
   dataset_size: 3341105554.6299996
 configs:
-- config_name: 30s
-  data_files:
-  - split: train
-    path: 30s/train-*
-  - split: validation
-    path: 30s/validation-*
-  - split: test
-    path: 30s/test-*
 - config_name: clean
   data_files:
   - split: train
@@ -109,14 +51,6 @@ configs:
     path: clean/validation-*
   - split: test
     path: clean/test-*
-- config_name: clean_extra
-  data_files:
-  - split: train
-    path: clean_extra/train-*
-  - split: validation
-    path: clean_extra/validation-*
-  - split: test
-    path: clean_extra/test-*
 - config_name: default
   data_files:
   - split: train
@@ -325,6 +259,57 @@ audio_dataset.push_to_hub(
     embed_external_files=True
 )
 ```
+#### Extra (without punctuations)
+Doing step 1-10, but reverse step 5 to look for ones without punctuations, this yields a small extra set:
+```python
+extra_set = {
+    "37s5xmYYSM8",
+    "3ZVVBEugui4",
+    "-zHxyIuEw-8",
+    "Dngt6Ca8-3u",
+    "zJcle9SO98Q",
+    "murJVhx5dd0",
+    "6hCLoOVtM5Y", # test
+    "U-1tallz0hM",
+    "wfCUHCYJgIU",
+    "GrKoml8qb78",
+    "YMTMTFpV7_M",
+    "GJV0ZRzAARy",
+    "BtMii9364Fg",
+    "apK8JYOq6gI",
+    "IF-GnMzu7y8",
+    "0qJ61eujIVo",
+    "Okq02I_jTcA",
+    "hCnZlSbTht8",
+    "rMk21JBTisE", # validation
+    "s9qzwyIM3JI",
+    "NBf6Z9R1r7I",
+    "jIbc2Jzfa0g",
+}
+```
+```
+train:
+20 videos
+validation:
+1 video
+test:
+1 video
+DatasetDict({
+    train: Dataset({
+        features: ['audio', 'text', 'id', 'session_id'],
+        num_rows: 5990
+    })
+    validation: Dataset({
+        features: ['audio', 'text', 'id', 'session_id'],
+        num_rows: 397
+    })
+    test: Dataset({
+        features: ['audio', 'text', 'id', 'session_id'],
+        num_rows: 282
+    })
+})
+```
+
 #### Data Cleaning
 1. The video `Pew9CK74axu` is manually cleaned
 ```python
@@ -350,7 +335,88 @@ def manual_edit(batch):
 
 audio_dataset_manual = audio_dataset.map(manual_edit, batched=True, num_proc=8)
 ```
-2. General cleansing pipeline
+2. Low log-prob filtering
+Using whisper-medium to compute the logprob, then filter by a handpicked threshold `-3.5`
+```python
+# Get rid of low-prob videos
+low_prob_set = {
+    '9lQs7INyYBQ',
+    'HezOD6XPr_M',
+    'HfeLdctBVGY',
+    'IzfrgOUd2Uc',
+    'UFklIGGKWN0',
+    '_x8LwaPRtCE',
+    'eK9m6uCNN6Q',
+    'erbZNpDMHN0',
+    'l9BjfWr1_Pg',
+    'nSStWkJtbR4',
+    'wrEY_EzQEsy',
+    '3Zed0NHrmxo',
+    'r29FW7K4iok',
+    'MgdQuY0-abI',
+    'yHh4rM2KX5Q'
+}
+audio_dataset_manual = audio_dataset_manual.filter(lambda batch: [s not in low_prob_set for s in batch['session_id']], num_proc=2, batched=True)
+# 176 - 14 = 161 videos
+```
+3. train/dev/test split
+```python
+from datasets import DatasetDict
+
+validation_set = {
+    "AyPua3Mi9FU",
+    "r29FW7K4iok", # low prob
+    "GaUSbuZm5Ec",
+    "AKW9vmSy8lQ",
+    "3Zed0NHrmxo", # low prob
+    "ZHPFLOuT48u",
+    "RiCN24FLVLk",
+    "zrV_ZNWo8PQ",
+    # "rMk21JBTisE", # new (no punc) ==> not in 'default' config
+}
+test_set = {
+    "lH7bZ-8hF1o",
+    "WF4ovtdi6wu",
+    "MgdQuY0-abI", # low prob
+    "yHh4rM2KX5Q", # low prob
+    "e_cxHBDSqsM",
+    "NO6985Bf_Ro",
+    # "6hCLoOVtM5Y", # new (no punc) ==> not in 'default' config
+}
+
+def train_fn(batch):
+    return (z not in (validation_set|test_set) for z in batch['session_id'])
+def validation_fn(batch):
+    return (z in validation_set for z in batch['session_id'])
+def test_fn(batch):
+    return (z in test_set for z in batch['session_id'])
+
+audio_dataset_manual = DatasetDict(
+    train=audio_dataset_manual.filter(train_fn, num_proc=2, batched=True),
+    validation=audio_dataset_manual.filter(validation_fn, num_proc=2, batched=True),
+    test=audio_dataset_manual.filter(test_fn, num_proc=2, batched=True)
+)
+```
+Don't forget to merge with extra set
+```python
+from datasets import concatenate_datasets
+ds_extra = load_dataset("georgechang8/code_switch_yodas_zh", "clean_extra") # no longer available
+audio_dataset_manual = DatasetDict({
+    split: concatenate_datasets([audio_dataset_manual[split], ds_extra[split]])
+    for split in audio_dataset_manual
+})
+```
+Do sanity check
+```python
+ds_full = audio_dataset_manual
+for split in ds_full:
+    print(split, len(set(ds_full[split]['id'])))
+assert len(set(ds_full['train']['id']) & set(ds_full['validation']['id'])) == 0
+assert len(set(ds_full['train']['id']) & set(ds_full['test']['id'])) == 0
+assert len(set(ds_full['test']['id']) & set(ds_full['validation']['id'])) == 0
+```
+
+4. General cleansing pipeline
 ```python
 import re
 import html
@@ -380,12 +446,13 @@ def clean_transcripts(x):
     cjk = "[\u3400-\u4db5\u4e00-\u9fa5\u9fa6-\u9fbb\uf900-\ufa2d\ufa30-\ufa6a\ufa70-\ufad9\uff00-\uffef\u2e80-\u2eff\u3000-\u303f\u31c0-\u31ef\u2f00-\u2fdf\u2ff0-\u2fff\u3100-\u312f\u31a0-\u31bf\ufe10-\ufe1f\ufe30-\ufe4f\u2600-\u26ff\u2700-\u27bf\u3200-\u32ff\u3300-\u33ff]"
     x = html.unescape(x)
     x = remove_emojies(x)
-    dots = '\.{3,}'
-    x = re.sub(rf'{dots}|…|\s|^|$', '  ', x)   # expanding space allows matching " uh uh" case
+    x = re.sub(r'\.{3,}', ' ', x)
+    x = re.sub(r'…+', ' ', x)
+    x = re.sub(r'\s+|^|$', '  ', x) # expanding space allows matching " uh uh" case
     x = re.sub(rf"({cjk}|\s)([Uu][mh]|U[MH])({cjk}|\s)", r"\1 \3", x) # uh/um surrounded by cjk or space
     x = re.sub(r"([HhEe]mm+|[HE]MM+)", " ", x) # hmm emm
     x = re.sub(fr"\*+({cjk}+|[A-Za-z]+)\*+", " ", x)  # *叹气* 
-    x = re.sub(r'[呃嗯]', ' ', x)  # 呃嗯
+    x = re.sub(r'[呃嗯]+', ' ', x)  # 呃嗯
     def replace_except(pattern, repl, z, excs):
         for e, t in excs:
             z = z.replace(e, t)
@@ -395,21 +462,28 @@ def clean_transcripts(x):
         return z
     # remove 恩 except for 恩桥 感恩 恩怨
     x = replace_except("恩", ' ', x, excs=[("感恩", "呃"),("恩桥", "嗯"),("恩怨", "emm")])
-    # remove (...) except for 'Program Files (x86)'
-    x = re.sub(r'（[^（）]*）', ' ', x)
+    x = re.sub(r'（[^（）]*）', ' ', x)  # remove （...）
+    x = re.sub(r'[（）]+', ' ', x) # remove isolated（）
     x = re.sub(r"\s+", " ", x)
+    # remove (...) except for 'Program Files (x86)'
     x = replace_except(r'\([^()]*\)', ' ', x, excs=[("Program Files (x86)", "呃")])
-    puncs = r'[，？！。；?!,;~～]'
+    x = re.sub(r'[()]+', ' ', x) # remove isolated ()
+    puncs = r'[，？！。：；～?!,.:;~]'
     x = re.sub(rf'({puncs})(?:\s*\1)+', r'\1', x) # ？？？ -> ？
     x = re.sub(rf"\s+({puncs})", r'\1', x) # text , -> text,
-    sp_puncs = r'[?!,;]' # puncs with spaces
-    x = re.sub(rf"({puncs}*{sp_puncs})([a-zA-Z])", r'\1 \2', x) # text,cont -> text, cont
+    sp_puncs = r'[?!,.;]' # puncs with spaces
+    x = re.sub(rf"({puncs}*{sp_puncs})([^\d])", r'\1 \2', x) # text!?cont -> text!? cont
     x = re.sub(rf"^[\s]*{puncs}+", "", x) # leading puncs
     x = re.sub(r"\s+", " ", x) # excess spaces
     return x.strip()
 
-audio_dataset_manual_clean = audio_dataset_manual.map(lambda x: {"text": list(map(clean_transcripts, x['text']))}, batched=True, num_proc=8)
-# push to hub
+def clean_batch(batch):
+    return {'text': [clean_transcripts(x) for x in batch['text']]}
+
+audio_dataset_manual_clean = audio_dataset_manual.map(clean_batch, batched=True, num_proc=8)
+```
+4. Publish
+```python
 audio_dataset_manual_clean.push_to_hub(
     "georgechang8/code_switch_yodas_zh",
     config_name="clean",

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