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Update README.md
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README.md
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---
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# speechocean762: A non-native English corpus for pronunciation scoring task
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##
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```bash
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pip install datasets
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pip install librosa
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pip install soundfile
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```
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```python
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>>> from datasets import load_dataset
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'total': 9}
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```
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## Introduction
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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.
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This corpus aims to provide a free public dataset for the pronunciation scoring task.
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Key features:
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* It is available for free download for both commercial and non-commercial purposes.
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* The speaker variety encompasses young children and adults.
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* The manual annotations are in multiple aspects at sentence-level, word-level and phoneme-level.
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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.
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Five experts made the scores. To avoid subjective bias, each expert scores independently under the same metric.
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## The scoring metric
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The experts score at three levels: phoneme-level, word-level, and sentence-level.
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### Phoneme level
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Score the pronunciation goodness of each phoneme within the words.
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Score range: 0-2
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* 2: pronunciation is correct
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* 1: pronunciation is right but has a heavy accent
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* 0: pronunciation is incorrect or missed
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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.
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An example:
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```json
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{
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"text": "LISA",
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"accuracy": 5,
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"phones": ["L", "IY1", "S", "AH0"],
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"phones-accuracy": [0.4, 2, 2, 1.2],
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"mispronunciations": [
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{
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"canonical-phone": "L",
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"index": 0,
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"pronounced-phone": "D"
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}
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],
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"stress": 10,
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"total": 6
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}
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```
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### Word level
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Score the accuracy and stress of each word's pronunciation.
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#### Accuracy
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Score range: 0 - 10
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* 10: The pronunciation of the word is perfect
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* 7-9: Most phones in this word are pronounced correctly but have accents
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* 4-6: Less than 30% of phones in this word are wrongly pronounced
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* 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"
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* 1: The pronunciation is hard to distinguish
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* 0: no voice
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#### Stress
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Score range: {5, 10}
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* 10: The stress is correct, or this is a mono-syllable word
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* 5: The stress is wrong
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### Sentence level
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Score the accuracy, fluency, completeness and prosodic at the sentence level.
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* 3-4: Unstable speech speed, speak too fast or too slow, without the sense of rhythm
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* 0-2: Poor intonation and lots of stammering and pauses, unable to read a complete sentence
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"fluency": [10.0, 9.0, 8.0, 8.0, 10.0],
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"prosodic": [10.0, 9.0, 7.0, 8.0, 9.0],
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"total": [7.6, 9.0, 7.9, 8.0, 9.1],
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"words": [
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{
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"accuracy": [10.0, 10.0, 10.0, 10.0, 10.0],
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"stress": [10.0, 10.0, 10.0, 10.0, 10.0],
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"total": [10.0, 10.0, 10.0, 10.0, 10.0],
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"text": "WE",
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"ref-phones": "W IY0",
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"phones": ["W IY0", "W IY0", "W IY0", "W IY0", "W IY0"]
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},
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{
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"accuracy": [10.0, 8.0, 10.0, 10.0, 8.0],
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"stress": [10.0, 10.0, 10.0, 10.0, 10.0],
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"total": [10.0, 8.4, 10.0, 10.0, 8.4],
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"text": "CALL",
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"ref-phones": "K AO0 L",
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"phones": ["K AO0 L", "K {AO0} L", "K AO0 L", "K AO0 L", "K AO0 {L}"],
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},
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{
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"accuracy": [10.0, 10.0, 10.0, 10.0, 10.0],
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"stress": [10.0, 10.0, 10.0, 10.0, 10.0],
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"total": [10.0, 10.0, 10.0, 10.0, 10.0],
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"text": "IT",
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"ref-phones": "IH0 T",
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"phones": ["IH0 T", "IH0 T", "IH0 T", "IH0 T", "IH0 T"]
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},
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{
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"accuracy": [3.0, 7.0, 10.0, 2.0, 6.0],
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"stress": [10.0, 10.0, 10.0, 10.0, 10.0],
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"phones": ["B (EH0) (R)", "B {EH0} {R}", "B EH0 R", "B (EH0) (R)", "B EH0 [L] R"],
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"total": [4.4, 7.6, 10.0, 3.6, 6.8],
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"text": "BEAR",
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"ref-phones": "B EH0 R"
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}
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],
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},
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...
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}
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```
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* for score 0, use "()" symbol
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* for the inserted phone, use the "[]" symbol
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## Citation
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Please cite our paper if you find this work useful:
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---
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# speechocean762: A non-native English corpus for pronunciation scoring task
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+
## Introduction
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+
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.
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+
|
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+
This corpus aims to provide a free public dataset for the pronunciation scoring task.
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+
Key features:
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+
* It is available for free download for both commercial and non-commercial purposes.
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+
* The speaker variety encompasses young children and adults.
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+
* The manual annotations are in multiple aspects at sentence-level, word-level and phoneme-level.
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+
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+
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.
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+
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Five experts made the scores. To avoid subjective bias, each expert scores independently under the same metric.
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+
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## Uses
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```bash
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pip install datasets
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pip install librosa
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pip install soundfile
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```
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```python
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>>> from datasets import load_dataset
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'total': 9}
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```
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## The scoring metric
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The experts score at three levels: phoneme-level, word-level, and sentence-level.
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### Sentence level
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Score the accuracy, fluency, completeness and prosodic at the sentence level.
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* 3-4: Unstable speech speed, speak too fast or too slow, without the sense of rhythm
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90 |
* 0-2: Poor intonation and lots of stammering and pauses, unable to read a complete sentence
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+
### Word level
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+
Score the accuracy and stress of each word's pronunciation.
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+
#### Accuracy
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+
Score range: 0 - 10
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+
* 10: The pronunciation of the word is perfect
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+
* 7-9: Most phones in this word are pronounced correctly but have accents
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+
* 4-6: Less than 30% of phones in this word are wrongly pronounced
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+
* 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"
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* 1: The pronunciation is hard to distinguish
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* 0: no voice
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#### Stress
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Score range: {5, 10}
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* 10: The stress is correct, or this is a mono-syllable word
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* 5: The stress is wrong
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+
### Phoneme level
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Score the pronunciation goodness of each phoneme within the words.
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Score range: 0-2
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* 2: pronunciation is correct
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* 1: pronunciation is right but has a heavy accent
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* 0: pronunciation is incorrect or missed
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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.
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+
An example:
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```json
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{
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"text": "LISA",
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"accuracy": 5,
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"phones": ["L", "IY1", "S", "AH0"],
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"phones-accuracy": [0.4, 2, 2, 1.2],
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"mispronunciations": [
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{
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"canonical-phone": "L",
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"index": 0,
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"pronounced-phone": "D"
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}
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],
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"stress": 10,
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"total": 6
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}
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```
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## Citation
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Please cite our paper if you find this work useful:
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