Introducing Voice Agent: Real Time Voice Assistant for Language Models
- Adrian Araya
- Apr 29
- 4 min read
OpenAI recently introduced its real-time voice feature—bringing AI conversations one step closer to feeling truly human. It allows for natural, fluid dialogue where you can interrupt the assistant mid-sentence, just like in a real conversation. This breakthrough has opened the door to voice interfaces that respond instantly and adapt to the rhythm of human speech.
At RidgeRun ai, we took this idea further and built Voice Agent—a fully on-premise, real-time voice assistant system designed for developers who want more control and flexibility. Whether for embedded platforms, desktop apps, or web interfaces, Voice Agent enables seamless conversations with LLMs, supporting natural interruption, real-time response, and full customization of audio pipelines—all without relying on cloud-only infrastructure.
Designed for Real-Time Conversations
Voice Agent is built to listen actively, understand natural speech, generate thoughtful responses using a language model, and reply out loud—all in one continuous, low-latency loop. And just like in a real conversation, you don’t have to wait for it to finish talking—you can interrupt at any moment, and it will listen again, instantly switching gears.
The system follows a clear, intuitive flow:
Detect when the user starts speaking.
Transcribe the speech to text.
Generate a smart response using a language model.
Synthesize and play the response using a human-like voice.
All of this happens automatically, in real time, and always ready to adjust mid-conversation.
Modular by Design
Each part of Voice Agent is its own component, giving you flexibility and control:
Audio Input: Supports standard microphones or WebRTC-based capture via FastRTC.
Voice Activity Detection: Detects when someone starts talking to initiate processing or interrupt the current LLM answer. It also detects when the talking is over to perform the conversation turnaround. The default implementation is powered by the Silero VAD model to detect when someone starts talking.
Memory: When voice activity is detected, the memory module starts buffering the audio containing valid conversational audio data. It also adds a small audio prefix in case part of the speech was lost at the starting boundary.
Cooldown: For a better conversation turnaround experience, this module allows for a configurable wiggle room for when silence is detected, in case the speaker resumes the conversation.
Transcription: Performs speech-to-text conversion of the buffered audio. The current implementation uses the Whisper model.
Language Model: Supports any OpenAI-compatible APIs, including self-hosted or open-source models like Ollama
Speech Synthesis: Converts text back into natural speech. The default implementation uses the Piper model.
Audio Output: Supports standard speaker or WebRTC-based audio send via FastRTC.
Each module runs as an asynchronous task, coordinated by a simple state machine that ensures smooth transitions from listening to speaking.
Configurable to Fit Your Needs
Voice Agent is easy to configure. Whether you need to change the sample rate, model type, cooldown period, or device source—just update the config file and you’re ready to go.
A few examples of what’s configurable:
Audio input device and sample rate.
Model used for VAD (Voice Activity Detection), transcription, and TTS (Text To Speech).
LLM prompt (for custom agent behavior), model and max response length.
Cooldown behavior between interactions.
This flexibility means you can adapt Voice Agent to fit different platforms, performance constraints, or interaction styles.
How to Use Voice Agent
Getting started with Voice Agent is simple. You can run it in different modes depending on your setup—local audio or WebRTC—and each offers a smooth voice interaction experience. Here’s how each option works:
Local Audio Mode
If you're running Voice Agent on a device with direct access to a microphone and speaker (like a desktop or embedded system), just launch the application from your terminal. Once it starts, it will begin listening automatically.
You don’t need to press anything—just speak. When you pause long enough (a configurable silence), the system will understand you're done talking, process your request, and respond out loud.
WebRTC Mode with FastRTC
If you're running Voice Agent in WebRTC mode, the application will launch a web interface at http://localhost:7860 by default (you can change the port if needed).
To begin interacting:
Open the URL in your browser.
Click the button labeled “Click to Access Microphone”.
Grant microphone access when prompted.
Speak normally—just as you would in any conversation.
This interface also includes mute controls for the microphone and speaker, giving you more flexibility over the interaction.
WebRTC is ideal for browser-based interactions, and it includes echo cancellation by default—so the system won’t accidentally pick up its own voice when responding.
🤗 Try It on Hugging Face
You can also try Voice Agent directly in your browser using our hosted demo:
It works exactly like the WebRTC version described above: click the stream box, allow microphone access, and start talking.
Why Voice Agent?
Whether you're building voice interfaces for smart devices, interactive kiosks, virtual assistants, or productivity tools, Voice Agent gives you:
A real-time, responsive voice interface.
Clean architecture with modular components.
Support for both cloud-based and local models.
An easy-to-integrate and fully configurable system.
Compatibility with embedded platforms like NVIDIA Jetson, making it ideal for edge AI applications where low latency and local processing are key.
It’s designed to help you create voice-powered experiences without starting from scratch.
🚀 Ready to Add Voice Intelligence to Your Product? Let’s Talk
If you're exploring how to integrate real-time voice interaction into your application—whether it's for embedded systems, smart assistants, or browser-based tools—we’d love to hear from you. Voice Agent is flexible, efficient, and designed to adapt to your architecture and goals.
Whether you’re just getting started or optimizing an existing voice pipeline, we can help you deploy a tailored voice interface powered by the latest in speech AI.
Reach out at support@ridgerun.ai — let’s build something that listens, thinks, and speaks with purpose.
It's fascinating how Voice Agent tackles the challenge of 'natural interruption' and 'real-time response' for on-premise LLM interactions. That level of control, especially with full customization of audio pipelines, is crucial for applications where data privacy or ultra-low latency are paramount. Considering the diverse platforms Voice Agent supports, from embedded to web, managing and optimizing the audio output format can become a practical consideration for developers. When dealing with various audio outputs, having reliable tools for converting audio to MP3 format can streamline workflows.