So you want to build your own private, voice-first AI platform with a custom text-to-speech (TTS) voice? That's a pretty awesome goal, & honestly, it's more achievable than ever before. Forget being tied to the big tech ecosystems & their data-hungry assistants. We're talking about creating something that's truly yours, from the wake word to the voice that talks back to you.
I've been down this rabbit hole, & let me tell you, it's a fascinating journey. It's part tinkering, part data science, & a whole lot of fun. This isn't just about privacy, though that's a HUGE part of it. It's about customization, about creating an AI that sounds like you, a celebrity, or a completely unique character you've dreamed up. It's about building a more personal & natural way to interact with your technology.
In this guide, I'm going to walk you through everything you need to know to build your own private, voice-first AI platform. We'll cover the core components, the open-source tools you'll need, & how to put it all together. So grab a coffee, get comfortable, & let's get started.
Before we dive into the "how," let's talk about the "why." Why go to all this trouble when you can just buy an off-the-shelf smart speaker?
For me, it boils down to three things: privacy, customization, & control.
Privacy: This is the big one. When you use a commercial voice assistant, your voice commands are sent to the cloud to be processed. That means your private conversations, your shopping lists, your random thoughts—they're all being stored & analyzed on someone else's servers. By building your own platform, you keep your data on your own hardware. Nothing leaves your home network unless you want it to.
Customization: With a private platform, you're not stuck with the default voices. You can create a custom TTS voice that's a perfect match for your brand, your personality, or your creative vision. Want your smart home to sound like GLaDOS from Portal? You can do that. Want to clone your own voice for a personalized assistant? Totally possible. We'll get into the nitty-gritty of that later.
Control: When you build your own system, you're in complete control. You decide what it can do, what it connects to, & how it behaves. You're not at the mercy of a company that might discontinue a feature or change its terms of service. You're the master of your own AI domain.
Alright, let's get technical. A voice-first AI platform is made up of three main components:
- Speech-to-Text (STT): This is the part of the system that listens to your voice & converts it into text. Think of it as the ears of your AI.
- Conversational AI/Large Language Model (LLM): This is the brains of the operation. It takes the text from the STT engine, figures out what you want, & generates a response.
- Text-to-Speech (TTS): This is the voice of your AI. It takes the text response from the conversational AI & turns it into spoken words.
These three components work together in a continuous loop: you speak, the STT engine transcribes, the conversational AI thinks, & the TTS engine responds.
Now, the trick to building a private platform is to have all three of these components running on your own hardware, or "on-premise." That's how you keep your data from being sent to the cloud.
Ready to get your hands dirty? Here's a step-by-step guide to building your own private, voice-first AI platform.
Step 1: Choose Your Hardware
First things first, you'll need some hardware to run your AI platform. You don't need a supercomputer, but you will need a machine with a decent amount of processing power. A dedicated machine is ideal, but you can also use a powerful desktop or a server you have lying around.
Here are a few options:
- A dedicated mini PC: Something like an Intel NUC or a similar machine is a great choice. They're small, quiet, & can be surprisingly powerful.
- A Raspberry Pi: While a Raspberry Pi can run a basic voice assistant, it might struggle with the more advanced models, especially if you want low latency. But it's a great place to start if you're on a budget.
- A home server: If you already have a home server for other things, you can probably use it to run your voice AI platform as well. Just make sure it has enough resources to handle the extra load.
You'll also need a microphone. A USB microphone like a Blue Yeti will work just fine. Or, if you want a more integrated solution, you can use a smart speaker like the ATOM Echo.
Step 2: Choose Your Privacy-Focused Framework
Next, you'll need a framework to tie everything together. This framework will act as the central hub for your STT, conversational AI, & TTS engines.
Here are a few great open-source, privacy-focused options:
Home Assistant: If you're building a voice assistant for your smart home, Home Assistant is an excellent choice. It's a powerful open-source home automation platform that has built-in support for voice assistants. You can easily integrate local STT & TTS engines, & it has a thriving community that's always creating new integrations.
Mycroft: Mycroft is one of the original open-source voice assistants. It's designed to be a private alternative to Alexa & Google Assistant. It's highly customizable & has a strong focus on privacy. You can even build your own "skills" to extend its functionality.
OpenVoiceOS (OVOS): OVOS is a community-driven fork of Mycroft. It's designed to be more modular & flexible than Mycroft, & it's a great choice for developers who want more control over their voice assistant.
LocalAI: LocalAI is a bit different. It's an open-source, OpenAI-compatible API that lets you run LLMs & other AI models locally. This is a great option if you're a developer who wants to build your own custom voice applications from the ground up.
For the rest of this guide, we'll focus on using Home Assistant, as it's a popular & well-documented choice for building a private voice assistant.
Step 3: Set Up Your On-Premise STT Engine
Now it's time to set up the "ears" of your AI. Your STT engine will transcribe your voice commands into text.
Here are a few on-premise STT options:
Whisper: Whisper is an open-source STT model from OpenAI that's incredibly accurate. You can run it locally on your own hardware, & it's a great choice for a private voice assistant. Home Assistant has a Whisper add-on that makes it easy to set up.
wav2vec 2.0: This is another powerful open-source STT model that you can run locally. It's a bit more complex to set up than Whisper, but it can be very accurate.
Picovoice: Picovoice is a commercial on-premise voice AI platform that offers a free tier for developers. It's a great option if you want a high-quality, reliable STT engine without the hassle of setting it up yourself.
This is where the magic happens. Your conversational AI, or LLM, is what will make your voice assistant "smart." It will take the transcribed text from your STT engine, understand what you want, & generate a response.
Here are a few options for running a conversational AI locally:
Ollama: Ollama is a platform that makes it easy to download & run various open-source LLMs on your local computer. You can use it to run models like Llama 2, Mistral, & others. Home Assistant has an Ollama integration that makes it easy to use these models as the brains of your voice assistant.
LocalAI: As mentioned earlier, LocalAI can also be used to run LLMs locally. It's a great option if you want more flexibility & control over your conversational AI.
When you're setting up your conversational AI, you'll need to give it a "personality." This is done through a system prompt, which is a set of instructions that tells the AI how to behave. You can tell it to be helpful, funny, sarcastic, or whatever you want. This is where you can really start to make your voice assistant your own.
Here at Arsturn, we're all about creating personalized AI experiences. That's why we've built a no-code platform that lets businesses create custom AI chatbots trained on their own data. These chatbots can provide instant customer support, answer questions, & engage with website visitors 24/7. It's all about creating a more meaningful connection with your audience, & that starts with a personalized AI.
Step 5: Create Your Custom TTS Voice
Now for the really fun part: creating a custom voice for your AI. This is what will give your voice assistant its unique personality.
There are a number of open-source TTS engines that support voice cloning, which is the process of creating a synthetic voice from a short audio sample. Here are a few of the most promising options:
XTTS-v2: This is a powerful open-source TTS model that can clone a voice from just a 6-second audio clip. It supports 17 languages & can even transfer emotion & style from the original audio. This is a great option for creating a high-quality, natural-sounding custom voice.
Zonos-v0.1: Zonos is another impressive open-source voice cloning model. It uses a diffusion-based neural vocoder to generate incredibly realistic speech. It's also designed to be highly customizable, making it a great choice for developers who want to fine-tune their TTS engine.
Chatterbox: Developed by Resemble AI, Chatterbox is a small, fast, & easy-to-use TTS model that supports AI voice cloning. It's known for its natural-sounding speech & its ability to control the emotional expressiveness of the generated voice.
Orpheus: Orpheus is a Llama-based TTS model that comes in various sizes, making it suitable for a wide range of hardware. It supports zero-shot voice cloning, guided emotion, & even real-time streaming.
To clone a voice, you'll need a short, clean audio sample of the voice you want to clone. The better the quality of the audio sample, the better the cloned voice will be. You can use a recording of your own voice, a clip from a movie, or any other audio you have the rights to use.
Once you have your audio sample, you'll need to use the tools provided by the TTS engine to train a new voice. The exact process will vary depending on the engine you choose, so be sure to consult the documentation.
Step 6: Integrate Everything with Your Framework
Now that you have all the components, it's time to put them all together. If you're using Home Assistant, this is a relatively straightforward process. You'll need to configure the Whisper & Ollama integrations, & then set up a new voice assistant pipeline that uses your custom TTS engine.
If you're using a different framework, you'll need to consult the documentation for instructions on how to integrate your STT, conversational AI, & TTS engines.
Step 7: Test & Refine
Once you have everything set up, it's time to start testing. Talk to your voice assistant, ask it questions, & see how it responds. Pay attention to the accuracy of the STT engine, the quality of the TTS voice, & the helpfulness of the conversational AI.
You'll probably need to do some fine-tuning to get everything working just right. You might need to adjust the microphone settings, tweak the system prompt for your conversational AI, or experiment with different TTS models.
This is an iterative process, so don't be afraid to experiment. The more you use your voice assistant, the more you'll learn about what works & what doesn't.
The Future is Private & Personalized
Building your own private, voice-first AI platform is a rewarding project that will give you a new appreciation for the power of AI. It's a chance to take back control of your data, create a truly personalized experience, & learn a ton along the way.
And this is just the beginning. As open-source AI models continue to get better & more accessible, the possibilities for private, personalized AI are only going to grow. We're moving towards a future where our technology understands us, speaks in our voice, & works for us, not for some faceless corporation.
Here at Arsturn, we're excited to be a part of that future. We believe that AI should be accessible to everyone, & that it should be used to create more meaningful & personalized experiences. That's why we're building tools that empower businesses to create their own custom AI chatbots, trained on their own data, to boost conversions & provide personalized customer experiences.
So go ahead, build your own private voice assistant. Experiment, tinker, & have fun. The future of voice is in your hands.
Hope this was helpful! Let me know what you think.