Nathaniel Okenwa
Hello JARVIS - Building Voice Interfaces for Your LLMS
#1about 2 minutes
Introduction to building JARVIS-like voice interfaces
The goal of building a sophisticated voice AI assistant like Iron Man's JARVIS is now more achievable thanks to modern technologies.
#2about 5 minutes
Why natural voice AI has been so difficult
Fictional AI assistants set a high bar for natural voice interaction that early real-world technologies like Siri failed to meet until the arrival of LLMs.
#3about 3 minutes
Navigating the uncanny valley of AI conversations
To avoid the unsettling 'uncanny valley' in voice AI, systems must handle non-linear conversations, interruptions, and the subtle timing of human speech.
#4about 3 minutes
Architecting a composable text-based voice AI stack
A modern voice AI stack combines speech-to-text, an LLM, and text-to-speech, offering more control and better performance than current speech-to-speech models.
#5about 8 minutes
Live demo of handling user interruptions
The demo shows how to implement interruption handling by stopping the AI's audio output and feeding the context of the interruption back into the LLM prompt.
#6about 3 minutes
Using voice interstitials to manage processing delays
Voice interstitials are pre-emptive audio messages that inform the user an action is in progress, preventing the perception of a system failure during long tasks.
#7about 1 minute
Designing AI agents as a constellation of models
An effective voice AI system is not a single monolithic agent but a constellation of smaller, faster models for specific tasks like checking for wake words or playing interstitials.
#8about 2 minutes
Abstracting voice infrastructure with Twilio Conversation Relay
Twilio's Conversation Relay simplifies development by managing the complex audio pipeline, including speech-to-text, text-to-speech, and interruption handling, via a WebSocket API.
Related jobs
Jobs that call for the skills explored in this talk.
Matching moments
00:17 MIN
Building a custom voice AI with WebRTC and Google APIs
Raise your voice!
02:48 MIN
Tracing the evolution from LLMs to agentic AI
Exploring LLMs across clouds
25:55 MIN
Building real-time conversational agents
Prompt API & WebNN: The AI Revolution Right in Your Browser
00:04 MIN
Three pillars for integrating LLMs in products
Using LLMs in your Product
09:31 MIN
The core challenge of integrating voice technologies
Raise your voice!
18:11 MIN
Leveraging AI as a new user experience paradigm
You are not an AI developer
00:04 MIN
The evolution of NLP from early models to modern LLMs
Harry Potter and the Elastic Semantic Search
04:02 MIN
Building language-enabled universal interfaces for software
Semantic AI: Why Embeddings Might Matter More Than LLMs
Featured Partners
Related Videos
Three years of putting LLMs into Software - Lessons learned
Simon A.T. Jiménez
Using LLMs in your Product
Daniel Töws
AI: Superhero or Supervillain? How and Why with Scott Hanselman
Scott Hanselman
Bringing the power of AI to your application.
Krzysztof Cieślak
Beyond Chatbots: How to build Agentic AI systems
Philipp Schmid
AI & Ethics
PJ Hagerty
On a Secret Mission: Developing AI Agents
Jörg Neumann
Speak, Code, Deploy: Transforming Developer Experience with Voice Commands
Sami Ekblad
Related Articles
View all articles



From learning to earning
Jobs that call for the skills explored in this talk.



Agentic AI Architect - Python, LLMs & NLP
FRG Technology Consulting
Intermediate
Azure
Python
Machine Learning


Conversational AI & Machine Learning Engineer
Deloitte
Leipzig, Germany
Azure
DevOps
Python
Docker
PyTorch
+6

AI Engineer, London
Eloquent AI
Charing Cross, United Kingdom
€52K
Intermediate
Azure
React
Python
Node.js
+4

ML Engineering Manager Voice Models - ASR/STT
DOCTOLIB SAS
Canton de Levallois-Perret, France
Senior
Java
Swift
Python
Kotlin
PyTorch
+4

AI Engineer Workflows & Agents (e.g. with Langdock, n8n & make)
WaveSix Labs GmbH
Berlin, Germany
Intermediate
API
GIT
JSON
REST
Azure
+4
