Presenter Information

Michael KnightenFollow

Location

https://www.kennesaw.edu/ccse/events/computing-showcase/fa25-cday-program.php

Document Type

Event

Start Date

24-11-2025 4:00 PM

Description

Autumn Lite is an inspectable, small-footprint language modeling pipeline for reproducible experimentation and practical integration into video-game non-player character (NPC) systems. It comprises four components: (1) a regex-aware tokenizer/normalizer for vocabulary construction and mixed prose–code handling; (2) a classical evaluation track that reports perplexity to quantify predictive quality; (3) a compact neural language model (decoder-only Transformer) targeted at low latency and controllable outputs; and (4) a lightweight sentiment classifier (logistic regression) that assigns positive/neutral/negative tags to steer text-to-speech (TTS) prosody during NPC dialogue. By combining transparent preprocessing with baseline metrics and a small, deployable decoder, Autumn Lite aims to deliver predictable, designer-friendly behavior for NPC speech, enabling subtle, real-time adjustments to rate, pitch, and emphasis instead of monotone delivery. “This system operates as a standard small LLM and can be combined with NPC dialogue/TTS; in this presentation I will cover only the LLM portion.”

Share

COinS
 
Nov 24th, 4:00 PM

GRM-1145 Autumn Lite LLM

https://www.kennesaw.edu/ccse/events/computing-showcase/fa25-cday-program.php

Autumn Lite is an inspectable, small-footprint language modeling pipeline for reproducible experimentation and practical integration into video-game non-player character (NPC) systems. It comprises four components: (1) a regex-aware tokenizer/normalizer for vocabulary construction and mixed prose–code handling; (2) a classical evaluation track that reports perplexity to quantify predictive quality; (3) a compact neural language model (decoder-only Transformer) targeted at low latency and controllable outputs; and (4) a lightweight sentiment classifier (logistic regression) that assigns positive/neutral/negative tags to steer text-to-speech (TTS) prosody during NPC dialogue. By combining transparent preprocessing with baseline metrics and a small, deployable decoder, Autumn Lite aims to deliver predictable, designer-friendly behavior for NPC speech, enabling subtle, real-time adjustments to rate, pitch, and emphasis instead of monotone delivery. “This system operates as a standard small LLM and can be combined with NPC dialogue/TTS; in this presentation I will cover only the LLM portion.”