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DTSTART;TZID=America/Chicago:20260905T140000
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DTSTAMP:20260827T113821
CREATED:20260825T032941Z
LAST-MODIFIED:20260825T034849Z
UID:7260-1788616800-1788631200@cypressislamiccenter.org
SUMMARY:Build Your Own VoiceAI on the Edge: A Hands-On Workshop with ASR\, Local LLMs\, and Speech Synthesis
DESCRIPTION:Voice interfaces are becoming a core part of modern applications\, but most implementations rely heavily on cloud services for speech recognition\, inference\, and speech synthesis. While convenient\, this architecture introduces latency\, operational cost\, and privacy concerns that can make it unsuitable for many environments. \nIn this hands-on workshop\, participants will build a fully local VoiceAI pipeline using open-source tools that run entirely on their own machine. By the end of the session\, attendees will have a working system that captures spoken audio\, converts it to text\, runs inference using a local language model\, and responds with synthesized speech\, all without using external APIs. \nThe workshop will guide participants through setting up llama.cpp for local inference\, configuring speech-to-text and text-to-speech pipelines\, and exposing the model through a local HTTPS endpoint that can be tested using tools like Postman. \nRather than focusing on theory\, this workshop emphasizes practical implementation. Attendees will write and run the code themselves\, explore the architecture of a modular voice pipeline\, and experiment with model tuning and performance tradeoffs when running AI workloads on consumer hardware. \nParticipants will leave with a working VoiceAI prototype and a deeper understanding of how open-source tools can be used to build privacy-first\, edge-based AI systems. \nWhat Participants Will Build: \nDuring the workshop\, participants will build a working offline VoiceAI assistant with the following capabilities: \n\nCapture spoken audio from a microphone\nConvert speech to text using a local STT pipeline\nRun prompts through a locally hosted LLM\nConvert generated responses to speech\nPlay the response back to the user\nExpose the inference engine through an HTTPS endpoint for external clients\n\nThe final system will run entirely on the participant’s laptop. \nWorkshop Agenda\nPart 1 — Edge AI and Voice System Architecture\nWe begin by walking through the architecture of a local VoiceAI system and why edge-based inference is becoming increasingly practical. \nTopics covered:\n– VoiceAI pipeline design\n– Local vs cloud inference tradeoffs\n– Overview of the tools used in the workshop\n– How the components interact \nParticipants will also review the architecture diagram that the rest of the workshop builds toward. \nPart 2 — Running a Local LLM\nParticipants will install and run a local language model using llama.cpp. \nHands-on steps include:\n– Downloading and running a quantized LLM\n– Running the inference server from the command line\n– Exposing the model through an HTTP API\n– Testing prompts using curl and Postman \nParticipants will learn how to treat the LLM as a service that other components can interact with. \nPart 3 — Speech-to-Text Integration\nNext\, participants will add a local speech-to-text pipeline. \nHands-on exercises include:\n– Capturing microphone input\n– Converting audio to text\n– Sending transcripts to the LLM server\n– Inspecting responses \nThis step establishes the first half of the voice interaction loop. \nBreak\nPart 4 — Text-to-Speech Integration\nParticipants will add speech synthesis using Piper to generate spoken responses. \nHands-on exercises include:\n– Installing and running Piper\n– Generating speech from model responses\n– Playing synthesized audio locally\n– Testing voice responses \nAt this point\, participants will have a complete speech → inference → speech loop running locally. \nPart 5 — Exposing the LLM via HTTPS\nIn this section\, participants will add a lightweight reverse proxy in front of the LLM server. \nTopics covered:\n– Running a local HTTPS endpoint\n– Routing requests to the inference server\n– Testing with Postman and external tools\n– Security considerations for local AI services \nPart 6 — Performance Tuning and Extensions\nThe workshop concludes with practical guidance on improving the system. \nTopics include:\n– Model size vs latency tradeoffs\n– Prompt tuning\n– Streaming responses\n– Extending the architecture for real applications \nParticipants will also explore ideas for turning their prototype into a full product or research project. \nLearning Outcomes:\nBy the end of the workshop\, participants will be able to:\n– Run a local LLM using open-source tools\n– Build a modular VoiceAI pipeline\n– Integrate speech recognition and speech synthesis locally\n– Expose local inference through an HTTPS API\n– Evaluate performance tradeoffs when running models on consumer hardware \nParticipants will also walk away with a working project they can extend after the conference. \nTarget Audience:\nThis workshop is designed for:\n– Software developers\n– Platform engineers\n– AI/ML practitioners\n– Architects exploring edge AI systems \nParticipants should have basic familiarity with Python and command-line tools. Prior machine learning experience is not required. \nPrerequisites\nParticipants should bring a laptop capable of running local models. \nRecommended environment:\n– macOS or Linux (Windows is ok too)\n– Python 3.10+\n– At least 16GB RAM\n– Git and basic CLI familiarity \nSetup instructions will be provided before the workshop to ensure attendees can start quickly. \nRegistration\nFirst Name *Last Name *Email Address *PhoneAI Experience *What is your experience with working with local LLMs\, VoiceAI\, Ollama\, or AI in general?Proficient (Work in AI industry)Intermediate (Use it at work or personal use)Beginner (Learning)What hardware device will you bring? *Apple MacBookWindowsLinuxOtherWhat is your experience with Microsoft .NET? *The client we will use is built in .NET MAUI. It is not required that you know about MAUI\, but preferred for this session.ProficientIntermediateBeginnerNot familiarWhat do you expect to get out of this webinar?Consent *Agree to the processing of your information for event organization purposes.Submit
URL:https://cypressislamiccenter.org/event/voice-ai-workshop/
LOCATION:TX
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260912T110000
DTEND;TZID=America/Chicago:20260912T133000
DTSTAMP:20260827T113821
CREATED:20260727T133832Z
LAST-MODIFIED:20260803T144450Z
UID:7171-1789210800-1789219800@cypressislamiccenter.org
SUMMARY:Minor and Major Signs of Day of Judgment
DESCRIPTION:An interactive workshop by Imam Arsalan Majid. \nRSVP: \nNumber of attendees (including yourself) *Attendee InformationName *Age *Add attendeeRemove attendeeParticipant Consent & Acknowledgment *By registering for this event\, I confirm the following: \nI consent to the collection and processing of my personal information for the purposes of event registration and organization. This information will not be shared or used for any other purpose. \nBy submitting this form\, I acknowledge that I have read\, understood\, and agree to the above terms. Email Address *Your receipt will be emailed to you at this email addressPhoneRegistration FeeYou will be charged $5/person for this registration. \nTotal Fee: ${calculation-1} Total Fee$Credit / Debit Card *Major / Minor Signs of Day of Judgment 8-8-26Submit
URL:https://cypressislamiccenter.org/event/signs-day-of-judgment/
LOCATION:Cypress Islamic Center\, 16103 Cypress Rosehill Rd.\, Cypress\, TX\, 77429\, United States
CATEGORIES:Community
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ORGANIZER;CN="CIC Sisters' Committee":MAILTO:CICSisters2@gmail.com
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