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 # TatarSCR: An Open-Source Tatar Speech Commands Dataset
 
-**Hugging Face Dataset Card**
+This repository contains an open-source Tatar speech commands dataset designed for IoT and robotics applications, along with a trained Keyword-MLP model for inference.  The dataset and model are described in the following paper:
 
-This dataset card describes the Tatar Speech Commands Dataset (TSCD), an open-source collection of speech commands in the Tatar language, designed for use in IoT and robotics applications.  The dataset was introduced in the following paper:
+## Dataset Summary
 
-**Paper:**
+This dataset comprises 3,547 one-second utterances of 35 commands commonly used in robotics, IoT, and smart systems.  The data was collected from 153 different speakers.
 
-[An Open-Source Tatar Speech Commands Dataset for IoT and Robotics Applications](https://www.techrxiv.org/users/682600/articles/1231801-an-open-source-tatar-speech-commands-dataset-for-iot-and-robotics-applications)
+| Feature          | Description                                  |
+|-----------------|----------------------------------------------|
+| Number of Commands | 35                                           |
+| Number of Utterances | 3,547                                        |
+| Number of Speakers | 153                                          |
+| Audio Length      | 1 second per utterance                       |
 
-**Summary:**
 
-The Tatar Speech Commands Dataset (TSCD) provides a valuable resource for researchers and developers working on speech recognition systems for the Tatar language.  It contains 3,547 one-second utterances of 35 commands commonly used in robotics, IoT, and smart systems, recorded from 153 different speakers.  A Keyword-MLP model, trained and tested on this dataset, is also provided.
+## Model Summary
 
+A Keyword-MLP model was trained on this dataset.  Pre-trained weights are provided, allowing for direct inference using either PyTorch or ONNX runtime.  The model was adapted from the Keyword-MLP repository ([https://github.com/AI-Research-BD/Keyword-MLP](https://github.com/AI-Research-BD/Keyword-MLP)).  Inference scripts are provided for both short (~1 second) audio clips and longer clips using a sliding window approach.
 
-**Dataset Statistics:**
 
-| Statistic          | Value      |
-|----------------------|-------------|
-| Number of Commands | 35          |
-| Number of Utterances | 3,547       |
-| Number of Speakers  | 153         |
-| Audio Length (per utterance) | 1 second    |
+## Citation
 
+If you use this dataset or model, please cite the following paper:
 
-**Related Repositories:**
-
-* **Dataset Repository:** [https://github.com/IS2AI/TatarSCR](https://github.com/IS2AI/TatarSCR)
-* **Keyword-MLP Model:** [https://github.com/AI-Research-BD/Keyword-MLP](https://github.com/AI-Research-BD/Keyword-MLP) (used for model training in this project)
-
+> Askat Kuzdeuov, Rinat Gilmullin, Bulat Khakimov, and Huseyin Atakan Varol. An Open-Source Tatar Speech Commands Dataset for IoT and Robotics Applications. TechRxiv. October 18, 2024, DOI: 10.36227/techrxiv.172926779.98914732/v1.
 
-**Citation:**
 
-> Askat Kuzdeuov, Rinat Gilmullin, Bulat Khakimov, and Huseyin Atakan Varol. An Open-Source Tatar Speech Commands Dataset for IoT and Robotics Applications. TechRxiv. October 18, 2024, DOI: 10.36227/techrxiv.172926779.98914732/v1.
+## Repository Link
 
+[https://github.com/IS2AI/TatarSCR](https://github.com/IS2AI/TatarSCR)