# GLM-ASR STT Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/glm-asr-stt
> Markdown URL: https://aitinkerers.org/technologies/glm-asr-stt.md
> Technology record last updated: 2026-03-13T13:39:53Z
> Generated: 2026-10-24T05:06:21Z

A multimodal speech-to-text framework leveraging General Language Model (GLM) architecture for high-accuracy, context-aware transcription.

GLM-ASR STT integrates the architectural strengths of the GLM-4 family to process audio signals through a unified tokenization strategy. Developed by the THUDM team at Tsinghua University, this system moves beyond traditional acoustic modeling by treating speech as a primary linguistic modality. It excels in complex environments (noisy offices or multi-speaker dialogues) where context is critical for disambiguation. By utilizing a transformer-based backbone with billions of parameters, GLM-ASR delivers low-latency transcription that maintains semantic coherence across long-form recordings.

- Official technology site: https://github.com/THUDM/GLM-4
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [UnaMentis: A mobile, AI, voice first learning platform](https://portland.aitinkerers.org/talks/rsvp_L4vjfVilvoQ)

- Event context: AI Tinkerers Portland: Building Voice Agents & Conversational AI Stacks — 2026-03-06 — Portland
- Public talk page: https://portland.aitinkerers.org/talks/rsvp_L4vjfVilvoQ

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