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README.md
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language:
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- sr
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metrics:
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type: wer
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value: 0.0
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base_model:
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- facebook/wav2vec2-large-xlsr-53
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pipeline_tag: audio-classification
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language:
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- sr
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metrics:
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- wer
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base_model:
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- facebook/wav2vec2-large-xlsr-53
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pipeline_tag: audio-classification
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tags:
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- voice-command
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- smart-home
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- voice-controller
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- serbian-wav2vec
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- audio-classification
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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Smart home controller simulator, receiving voice commands from a microphone.
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Trained to detect the words: "vrata", "svetlo", "zvuk", "otvori", "zatvori", "uključi" and "isključi" to control the state of door, lights and audio in a smart home system.
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## Model Details
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### Model Description
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- **Developed by:** [Mihailo Radović](https://www.linkedin.com/in/mihailo-radović-484070278/)
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- **Model type:** Audio Classification (Smart home controller)
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- **Language(s) (NLP):** Serbian
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- **License:** MIT
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- **Finetuned from model:** facebook/wav2vec2-large-xlsr-53
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### Model Sources
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<!-- Provide the basic links for the model. -->
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- **Repository:** [GitHub Repo](https://github.com/mradovic38/voice-command-recognition)
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- **Demo:** [Streamlit App](https://smart-home-serbian-voice-controller.streamlit.app)
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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Detecting a word said in a short audio clip: "vrata", "svetlo", "zvuk", "otvori", "zatvori", "uključi" and "isključi" to control the state of door, lights and audio in a smart home system.
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### Out-of-Scope Use
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Works the best for the words that are in the dataset. For the words that are out of the vocabulary, the DTW check is implemented (see code in [GitHub Repo](https://github.com/mradovic38/voice-command-recognition)).
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## How to Get Started with the Model
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Check out the explaination in my [GitHub repository](https://github.com/mradovic38/voice-command-recognition) README file.
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