Cleanup README
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README.md
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@@ -8,33 +8,31 @@ This project integrates speech-to-text and text-to-speech functionalities into a
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## Features
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• Speech-to-Text and Text-to-Speech: Enables the car assistant to listen to spoken questions and respond audibly, providing a hands-free experience for drivers and passengers.
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• Intelligent Function Calling with NexusRaven: Implements a sophisticated system for executing commands and retrieving information based on user queries, using the LLaMA 2 model's capabilities.
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• Dynamic Model Integration: Incorporates multiple models for language recognition, speech processing, and text generation.
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• User-Friendly Gradio Interface: easy-to-use interface for testing and deploying the speaking assistant within the car's infotainment system.
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• Real-Time Information Retrieval: Capable of integrating with various APIs to provide up-to-date information on weather, routes, points of interest, and more.
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## Requirements
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• Gradio for creating interactive interfaces
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• Hugging Face Transformers and additional ML models for speech and language processing
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• NexusRaven for complex function execution
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All required libraries and packages are directly loaded inside the notebook.
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## Installation
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To set up the speaking assistant in your car's system, follow these steps:
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1. Run all the cells until the “Interfaces (text and audio)” section.
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2. Choose between the interfaces which one to run: audio-to-audio or text-to-text.
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Usage
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1. Model Setup: Begin by loading the necessary models for speech recognition, language processing, and text-to-speech conversion as detailed in the "Models loads" section.
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2. Function Definition: Customize the assistant's responses and capabilities by defining functions in the "Function calling with NexusRaven" section.
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3. Interface Configuration: Choose the Gradio interface that suits your in-car system, following setup instructions in the "Interfaces (text and audio)" section.
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4. Activation: Execute one of the interface to start the speaking assistant, enabling vocal interactions within the car.
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## Authors and acknowledgment
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Sasan Jafarnejad
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Abigail Berthe--Pardo
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## Features
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• Speech-to-Text and Text-to-Speech: Enables the car assistant to listen to spoken questions and respond audibly, providing a hands-free experience for drivers and passengers.
|
12 |
+
• Intelligent Function Calling with NexusRaven: Implements a sophisticated system for executing commands and retrieving information based on user queries, using the LLaMA 2 model's capabilities.
|
13 |
+
• Dynamic Model Integration: Incorporates multiple models for language recognition, speech processing, and text generation.
|
14 |
+
• User-Friendly Gradio Interface: easy-to-use interface for testing and deploying the speaking assistant within the car's infotainment system.
|
15 |
• Real-Time Information Retrieval: Capable of integrating with various APIs to provide up-to-date information on weather, routes, points of interest, and more.
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## Requirements
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• Gradio for creating interactive interfaces
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+
• Hugging Face Transformers and additional ML models for speech and language processing
|
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+
• NexusRaven for complex function execution
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All required libraries and packages are directly loaded inside the notebook.
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## Installation
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|
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+
To set up the speaking assistant in your car's system, follow these steps:
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1. Run all the cells until the “Interfaces (text and audio)” section.
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+
2. Choose between the interfaces which one to run: audio-to-audio or text-to-text.
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### Usage
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1. Model Setup: Begin by loading the necessary models for speech recognition, language processing, and text-to-speech conversion as detailed in the "Models loads" section.
|
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2. Function Definition: Customize the assistant's responses and capabilities by defining functions in the "Function calling with NexusRaven" section.
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3. Interface Configuration: Choose the Gradio interface that suits your in-car system, following setup instructions in the "Interfaces (text and audio)" section.
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4. Activation: Execute one of the interface to start the speaking assistant, enabling vocal interactions within the car.
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## Authors and acknowledgment
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Sasan Jafarnejad
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+
Abigail Berthe--Pardo
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