Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
Malayalam
Size:
1K - 10K
DOI:
License:
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Add dataset details
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README.md
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## Dataset Description
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- **Homepage: https://smc.org.in**
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- **Repository: https://gitlab.com/smc/msc-reviewed-speech**
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- **Leaderboard:**
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- **Point of Contact: Kavya Manohar**
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### Dataset Summary
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[More Information Needed]
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### Supported Tasks and Leaderboards
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### Languages
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## Dataset Structure
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### Data Instances
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[More Information Needed]
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### Data Fields
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[More Information Needed]
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### Data Splits
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## Dataset Creation
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[More Information Needed]
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###
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#### Initial Data Collection and Normalization
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[More Information Needed]
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[More Information Needed]
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### Personal and Sensitive Information
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## Considerations for Using the Data
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### Social Impact of Dataset
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### Discussion of Biases
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### Other Known Limitations
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## Additional Information
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### Dataset Curators
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### Licensing Information
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### Citation Information
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[More Information Needed]
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### Contributions
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[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## Dataset Description
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- **Homepage: [SMC](https://smc.org.in)**
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- **Repository: https://gitlab.com/smc/msc-reviewed-speech**
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- **Blog Post: https://blog.smc.org.in/malayalam-speech-corpus/**
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- **Leaderboard:**
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- **Point of Contact: Kavya Manohar**
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### Dataset Summary
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- 1541 speech samples
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- 75 speech contributors
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- 1:38:16 hours of speech
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- 482 unique sentences
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- 1400 unique words
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- 553 unique syllables
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- 48 unique phonemes
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For more detailed analysis see the python notebook provided [here](https://gitlab.com/smc/msc-reviewed-speech/-/blob/master/analysis/EDA.ipynb)
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### Supported Tasks and Leaderboards
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Automatic Speech Recognition system development, gender and age identification of speakers
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### Languages
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Malayalam
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## Dataset Structure
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- file_name
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- speechid
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- speaker_id
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- review_score
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- transcript
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- category (optional speech category)
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- speaker_gender (optionally self declared)
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- speaker_age (optionally self declared)
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### Data Instances
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### Data Fields
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### Data Splits
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So specific Splits
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## Dataset Creation
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The speech data is collected from volunteer users who read and record their speech through a [web application](https://msc.smc.org.in) using their personal devices. The recorded speech is reviewed (upvote and downvote gives a score of +1 and -1 respectively) by other users. The review score is also published.
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### Curation Rationale
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The recorded speech is reviewed (upvote and downvote gives a score of +1 and -1 respectively) by other users. The review score is also published.
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### Curation Rationale
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Those speech samples with at least three positive reviews are included in this dataset.
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### Source Data
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#### Initial Data Collection and Normalization
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The speech data is collected from volunteer contributors who read and record their speech through a [web application](https://msc.smc.org.in). The users optionally provide name, age and gender. There is no further verification. Sentences to read out are curated by MSC Admin. The speech samples are reviewed by other users.
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### Personal and Sensitive Information
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Every speaker is identified by a unique alphanumeric id and age and gender are published if the speaker has voluntarily published them.
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## Considerations for Using the Data
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### Social Impact of Dataset
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Read speech corpus, recorded in natural environments by the users.
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### Dataset Curators
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Kavya Manohar
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### Licensing Information
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CC-BY-SA 4.0
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### Citation Information
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### Contributions
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http://msc.smc.org.in/
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