title: Give me links to free speech t - Perplexica
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created: 2025-03-24
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Give me links to free speech t - Perplexica

Give me links to free speech to text that can be linked to local ollama LLMs

Sources

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Answer

Free Speech-to-Text Tools Linked to Local LLMs

Several platforms offer free speech-to-text technology that can be integrated with local Large Language Models (LLMs). Here are some options:

1. Mozilla DeepSpeech

Description: Mozilla DeepSpeech is an open-source, offline speech recognition system powered by TensorFlow and trained on a large corpus of text data.
Local LLM Integration: Yes, it can be fine-tuned for local use cases using the provided codebase and training datasets.
Free Version: Available
Link:https://github.com/mozilla/DeepSpeech

2. Kalliope

Description: Kalliope is an open-source, Python-based speech recognition system that can be used for various applications, including voice assistants and chatbots.
Local LLM Integration: Yes, it supports integration with local LLMs using the provided API.
Free Version: Available
Link:https://github.com/kalliope-tech/kalliope

3. Jasper

Description: Jasper is an open-source, Python-based speech recognition system that can be used for various applications, including voice assistants and chatbots.
Local LLM Integration: Yes, it supports integration with local LLMs using the provided API.
Free Version: Available
Link:https://github.com/jasper-nlg/jasper
Description: Google Cloud Speech-to-Text is a cloud-based speech recognition service that can be used for various applications, including voice assistants and chatbots.
Local LLM Integration: Yes, it supports integration with local LLMs using the provided API and TensorFlow Lite.
Free Version: Limited free tier available
Link:https://cloud.google.com/speech-to-text

5. Microsoft Azure Speech Services (with Local LLM)

Description: Microsoft Azure Speech Services is a cloud-based speech recognition service that can be used for various applications, including voice assistants and chatbots.
Local LLM Integration: Yes, it supports integration with local LLMs using the provided API and TensorFlow Lite.
Free Version: Limited free tier available
Link:https://azure.microsoft.com/en-us/services/cognitive-services/speech-services/

Please note that while these platforms offer free versions or trials, some may have limitations on usage, storage, or processing power. Be sure to review the pricing and terms of each service before integrating them with your local LLM.

Additional Resources:

For more information on speech-to-text technology and its applications, refer to the following resources:
- 1 "Speech Recognition Technology" by IEEE Spectrum
- 2 "The State of Speech Recognition" by Voicebot.ai

These links provide a starting point for exploring free speech-to-text tools that can be linked to local LLMs. Be sure to review each platform's documentation and terms of service before integrating them with your project.

Next Steps:

Review the documentation and tutorials provided by each platform to learn more about their APIs, integration methods, and usage limitations.
Experiment with each platform to determine which one best suits your needs and requirements.
Consider reaching out to the community or support teams for each platform if you encounter any issues or have questions during the integration process.

What are the key differences between Mozilla DeepSpeech, Kalliope, and Jasper in terms of their speech recognition accuracy and local LLM integration capabilities?

Can I use these free speech-to-text tools for commercial applications, and if so, what are the limitations on usage and storage?

How do I fine-tune Mozilla DeepSpeech for my specific use case, and what resources are available to help me with this process?

What is the trade-off between using a cloud-based service like Google Cloud Speech-to-Text or Microsoft Azure Speech Services versus hosting a local LLM, in terms of cost, scalability, and reliability?