Update README.md

README.md

@@ -12,14 +12,26 @@ size_categories:
 ---
 # speechocean762: A non-native English corpus for pronunciation scoring task
 
-## Example
+## Introduction
+Pronunciation scoring is a crucial technology in computer-assisted language learning (CALL) systems. The pronunciation quality scores might be given at phoneme-level, word-level, and sentence-level for a typical pronunciation scoring task.
+
+This corpus aims to provide a free public dataset for the pronunciation scoring task.
+Key features:
+* It is available for free download for both commercial and non-commercial purposes.
+* The speaker variety encompasses young children and adults.
+* The manual annotations are in multiple aspects at sentence-level, word-level and phoneme-level.
+
+This corpus consists of 5000 English sentences. All the speakers are non-native, and their mother tongue is Mandarin. Half of the speakers are Children, and the others are adults. The information of age and gender are provided.
+
+Five experts made the scores. To avoid subjective bias, each expert scores independently under the same metric.
+
+## Uses
 ```bash
 pip install datasets
 pip install librosa
 pip install soundfile
 ```
 
-
 ```python
 >>> from datasets import load_dataset
 
@@ -44,69 +56,9 @@ pip install soundfile
  'total': 9}
 ```
 
-## Introduction
-Pronunciation scoring is a crucial technology in computer-assisted language learning (CALL) systems. The pronunciation quality scores might be given at phoneme-level, word-level, and sentence-level for a typical pronunciation scoring task.
-
-This corpus aims to provide a free public dataset for the pronunciation scoring task.
-Key features:
-* It is available for free download for both commercial and non-commercial purposes.
-* The speaker variety encompasses young children and adults.
-* The manual annotations are in multiple aspects at sentence-level, word-level and phoneme-level.
-
-This corpus consists of 5000 English sentences. All the speakers are non-native, and their mother tongue is Mandarin. Half of the speakers are Children, and the others are adults. The information of age and gender are provided.
-
-Five experts made the scores. To avoid subjective bias, each expert scores independently under the same metric.
-
-
 ## The scoring metric
 The experts score at three levels: phoneme-level, word-level, and sentence-level.
 
-### Phoneme level
-Score the pronunciation goodness of each phoneme within the words.
-
-Score range: 0-2
-* 2: pronunciation is correct
-* 1: pronunciation is right but has a heavy accent
-* 0: pronunciation is incorrect or missed
-
-For the phones with an accuracy score lower than 0.5, an extra "mispronunciations" indicates which is the most likely phoneme that the current phone was actually pronounced.
-An example:
-
-```json
-{
-    "text": "LISA",
-    "accuracy": 5,
-    "phones": ["L", "IY1", "S", "AH0"],
-    "phones-accuracy": [0.4, 2, 2, 1.2],
-    "mispronunciations": [
-        {
-            "canonical-phone": "L",
-            "index": 0,
-            "pronounced-phone": "D"
-        }
-    ],
-    "stress": 10,
-    "total": 6
-}
-```
-
-### Word level
-Score the accuracy and stress of each word's pronunciation.
-
-#### Accuracy
-Score range: 0 - 10
-* 10: The pronunciation of the word is perfect
-* 7-9: Most phones in this word are pronounced correctly but have accents
-* 4-6: Less than 30% of phones in this word are wrongly pronounced
-* 2-3: More than 30% of phones in this word are wrongly pronounced. In another case, the word is mispronounced as some other word. For example, the student mispronounced the word "bag" as "bike"
-* 1: The pronunciation is hard to distinguish
-* 0: no voice
-
-#### Stress
-Score range: {5, 10}
-* 10: The stress is correct, or this is a mono-syllable word
-* 5: The stress is wrong
-
 ### Sentence level
 Score the accuracy, fluency, completeness and prosodic at the sentence level.
 
@@ -137,68 +89,51 @@ Score range: 0 - 10
 * 3-4: Unstable speech speed, speak too fast or too slow, without the sense of rhythm
 * 0-2: Poor intonation and lots of stammering and pauses, unable to read a complete sentence
 
-## The original scores
+### Word level
+Score the accuracy and stress of each word's pronunciation.
 
-The all five experts' original scores could be found in `resource/raw-scores.json`. An example item:
-```
-{
-    "000010011": {
-
-        "text": "WE CALL IT BEAR",
-        "accuracy": [7.0, 9.0, 8.0, 8.0, 9.0],
-        "completeness": [1.0, 1.0, 1.0, 1.0, 1.0],
-        "fluency": [10.0, 9.0, 8.0, 8.0, 10.0],
-        "prosodic": [10.0, 9.0, 7.0, 8.0, 9.0],
-        "total": [7.6, 9.0, 7.9, 8.0, 9.1],
-        "words": [
-            {
-                "accuracy": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "stress": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "total": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "text": "WE",
-                "ref-phones": "W IY0",
-                "phones": ["W IY0", "W IY0", "W IY0", "W IY0", "W IY0"]
-            },
-            {
-                "accuracy": [10.0, 8.0, 10.0, 10.0, 8.0],
-                "stress": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "total": [10.0, 8.4, 10.0, 10.0, 8.4],
-                "text": "CALL",
-                "ref-phones": "K AO0 L",
-                "phones": ["K AO0 L", "K {AO0} L", "K AO0 L", "K AO0 L", "K AO0 {L}"],
-            },
-            {
-                "accuracy": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "stress": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "total": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "text": "IT",
-                "ref-phones": "IH0 T",
-                "phones": ["IH0 T", "IH0 T", "IH0 T", "IH0 T", "IH0 T"]
-            },
-            {
-                "accuracy": [3.0, 7.0, 10.0, 2.0, 6.0],
-                "stress": [10.0, 10.0, 10.0, 10.0, 10.0],
-                "phones": ["B (EH0) (R)", "B {EH0} {R}", "B EH0 R", "B (EH0) (R)", "B EH0 [L] R"],
-                "total": [4.4, 7.6, 10.0, 3.6, 6.8],
-                "text": "BEAR",
-                "ref-phones": "B EH0 R"
-            }
-        ],
-    },
-    ...
-}
-```
+#### Accuracy
+Score range: 0 - 10
+* 10: The pronunciation of the word is perfect
+* 7-9: Most phones in this word are pronounced correctly but have accents
+* 4-6: Less than 30% of phones in this word are wrongly pronounced
+* 2-3: More than 30% of phones in this word are wrongly pronounced. In another case, the word is mispronounced as some other word. For example, the student mispronounced the word "bag" as "bike"
+* 1: The pronunciation is hard to distinguish
+* 0: no voice
 
-In this file, the phoneme-level scores are notated in the following convenient notation:
+#### Stress
+Score range: {5, 10}
+* 10: The stress is correct, or this is a mono-syllable word
+* 5: The stress is wrong
 
-* for score 2, do not use any symbol
-* for score 1, use "{}" symbol
-* for score 0, use "()" symbol
-* for the inserted phone, use the "[]" symbol
+### Phoneme level
+Score the pronunciation goodness of each phoneme within the words.
 
+Score range: 0-2
+* 2: pronunciation is correct
+* 1: pronunciation is right but has a heavy accent
+* 0: pronunciation is incorrect or missed
+
+For the phones with an accuracy score lower than 0.5, an extra "mispronunciations" indicates which is the most likely phoneme that the current phone was actually pronounced.
+An example:
 
-For example, "B (EH) R" means the score of EH is 0 while the scores of B and R are both 2,
-"B EH [L] R" mean there is an unexpected phone "L" and the other phones are scored 2.
+```json
+{
+    "text": "LISA",
+    "accuracy": 5,
+    "phones": ["L", "IY1", "S", "AH0"],
+    "phones-accuracy": [0.4, 2, 2, 1.2],
+    "mispronunciations": [
+        {
+            "canonical-phone": "L",
+            "index": 0,
+            "pronounced-phone": "D"
+        }
+    ],
+    "stress": 10,
+    "total": 6
+}
+```
 
 ## Citation
 Please cite our paper if you find this work useful: