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suryanshsk / Python-Voice-Assistant-Suryanshsk

A Python-based virtual assistant using Gemini AI. Features include voice recognition, text-to-speech, weather updates, news retrieval, jokes, Wikipedia info, and music management. Comes with an interactive web interface. Easily extendable and customizable.
MIT License
40 stars 110 forks source link

Enhanced Voice Interaction #3

Open Celestialbotics opened 1 month ago

Celestialbotics commented 1 month ago

Improve voice recognition accuracy by integrating advanced NLP models and adding support for multiple languages.

suryanshsk commented 1 month ago

Hi , For Issue #3

Thank you for your suggestion to improve voice recognition accuracy by integrating advanced NLP models and adding support for multiple languages. This is an excellent idea and would greatly enhance the capabilities of the project.

You're welcome to take on this issue as a GSSoC contributor. Here are some next steps to get started:

  1. Research and select appropriate NLP models (such as BERT, GPT, or others) to enhance voice recognition accuracy.
  2. Implement multilingual support, allowing the system to recognize and process multiple languages based on user preference or input detection.
  3. Ensure that the system remains lightweight and efficient to maintain performance after the integration of advanced models.
  4. Provide clear documentation outlining how the system supports multiple languages and detailing any new dependencies.

Feel free to reach out if you need further guidance or have any questions. Looking forward to seeing your contributions!

Best regards, Avanish Singh, Project Admin, GSSoC

On Tue, 1 Oct, 2024, 10:05 pm Celestialbotics, @.***> wrote:

Improve voice recognition accuracy by integrating advanced NLP models and adding support for multiple languages.

— Reply to this email directly, view it on GitHub https://github.com/suryanshsk/Python-Voice-Assistant-Suryanshsk/issues/3, or unsubscribe https://github.com/notifications/unsubscribe-auth/AVBBZFIJBZYPBSHPS7IABMLZZLFNRAVCNFSM6AAAAABPF6524GVHI2DSMVQWIX3LMV43ASLTON2WKOZSGU2TSNZSGMYDONY . You are receiving this because you are subscribed to this thread.Message ID: @.***>

Rajesh9998 commented 1 month ago

For improved multilingual support and faster voice recognition, I suggest leveraging the OpenAI Whisper Large V3 model through the Groq API. This approach would provide a more efficient solution than integrating advanced NLP models. The Whisper Large V3 model runs at an impressive speed factor of 164x, allowing for rapid transcriptions while maintaining high accuracy. This makes it ideal for applications requiring quick and reliable speech recognition across multiple languages. By utilizing Groq's infrastructure, we can ensure that our system remains lightweight and efficient, which is crucial for performance. I believe this method aligns well with our goals of enhancing voice recognition capabilities without compromising system efficiency. Let me know your thoughts!

Celestialbotics commented 1 month ago

Hi @Rajesh9998, Thank you for your suggestion to leverage the OpenAI Whisper Large V3 model through the Groq API. After reviewing the approach, I believe this is an excellent solution for improving multilingual support and maintaining system efficiency. The impressive speed factor of 164x is particularly appealing for real-time voice recognition, and its high accuracy will be essential for handling multiple languages. I agree that using Groq’s infrastructure will help us achieve the balance between performance and functionality without compromising the system's lightweight nature. I’m excited to proceed with this method and will begin integrating Whisper Large V3 into the system.

Celestialbotics commented 1 month ago

Hi @suryanshsk, Thank you for the detailed next steps. After evaluating the options, I’ll be leveraging the OpenAI Whisper Large V3 model through the Groq API for multilingual support and faster voice recognition, as this method aligns better with our goals of maintaining system efficiency.

Regarding your guidance:

  1. I’ll proceed with integrating Whisper for improved voice recognition and multilingual capabilities.
  2. I'll ensure the system remains lightweight while implementing these changes.
  3. Clear documentation will be provided detailing the dependencies and multilingual support.
  4. Could you please confirm if there are any specific datasets or other resources I should use for testing the voice recognition models? Let me know if you have any preferences or further guidance on that.

Looking forward to your feedback!

Best regards, Vaibhav

suryanshsk commented 1 month ago

Yes, please proceed.

On Thu, 3 Oct 2024 at 19:19, Celestialbotics @.***> wrote:

Hi @suryanshsk https://github.com/suryanshsk, Thank you for the detailed next steps. After evaluating the options, I’ll be leveraging the OpenAI Whisper Large V3 model through the Groq API for multilingual support and faster voice recognition, as this method aligns better with our goals of maintaining system efficiency.

Regarding your guidance:

  1. I’ll proceed with integrating Whisper for improved voice recognition and multilingual capabilities.
  2. I'll ensure the system remains lightweight while implementing these changes.
  3. Clear documentation will be provided detailing the dependencies and multilingual support.
  4. Could you please confirm if there are any specific datasets or other resources I should use for testing the voice recognition models? Let me know if you have any preferences or further guidance on that.

Looking forward to your feedback!

Best regards, Vaibhav

— Reply to this email directly, view it on GitHub https://github.com/suryanshsk/Python-Voice-Assistant-Suryanshsk/issues/3#issuecomment-2391475155, or unsubscribe https://github.com/notifications/unsubscribe-auth/AVBBZFKD6IZPJJXROCZ745LZZVDMZAVCNFSM6AAAAABPF6524GVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDGOJRGQ3TKMJVGU . You are receiving this because you were mentioned.Message ID: @.*** com>