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license: c-uda |
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--- |
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## 1. Introduction |
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Introducing a novel accent database "IndicAccentDB" which satisfies the below requirements: |
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* **Gender balance:** The speech database should be a collection of a wide range of speakers balancing both the male and female speakers to display the characteristics of the speakers speech. |
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* **Phonetically balanced uniform content:** To make the classification task simpler and models to distinguish the speakers, we considered building the IndicAccentDB with uniform content, a collection of speech recordings for |
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the Harvard sentences. These sentences gather intrinsic information by combining different phonemes and grammatically focused vocabulary. These sentences are appropriately expressing accents in sentence-level discourse. |
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You can access the Harvard sentences (sample shown below) dataset here: [Harvard Sentences](https://www.cs.columbia.edu/~hgs/audio/harvard.html) recited by the speakers in the recordings. |
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*The juice of lemons makes fine punch.* |
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*The fish twisted and turned on the bent hook.* |
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* IndicAccentDB contains speech recordings in six non-native English accents of Gujarati, Hindi, Kannada, Malayalam, Tamil, and Telugu. We collected six non-native accents from volunteers who had strong non-native |
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English accents and were well-versed in speaking at least one Indian language. Each speaker was asked to recite the Harvard sentences. The Harvard sentences dataset consists of 72 sets |
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of ten sentences each and is phonetically balanced sentences that are neither too short nor too long. |
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## 2. Dataset Usage |
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To use the dataset in your Python program, refer to the following script: |
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```python3 |
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from datasets import load_dataset |
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accent_db = load_dataset("DarshanaS/IndicAccentDb") |
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``` |
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## 3. Publications |
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1. [S. Darshana, H. Theivaprakasham, G. Jyothish Lal, B. Premjith, V. Sowmya and K. Soman, "MARS: A Hybrid Deep CNN-based Multi-Accent Recognition System for English Language," 2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR), Hyderabad, India, 2022, pp. 1-6, doi: 10.1109/ICAITPR51569.2022.9844177.](https://ieeexplore.ieee.org/document/9844177) |
