This repository contains a 500-cluster K-means codebook for Whisper large-v3-turbo encoder representations, trained on Japanese audio from Lambda Audio Corpus. Each 1,280-dimensional audio frame can be assigned to its nearest cluster center to produce a discrete unit ID from 0 to 499. These IDs can be used as targets for speech representation learning. They are learned acoustic units, not text tokens or labeled phonemes. The codebook was trained on 18,000,004 sampled frames from 199.89 hours of accepted audio. The repository includes the cluster centers, training features, and metadata. Original audio and transcripts are not included. The files are stored under codebook/. Only centroids.npy…