Tokenize training transcripts by grapheme (cluster) instead of codepoint

Description

This issue does not include a description.

Contributor guide

Tech stack

pythontensorflow

Domain

machine learning

Issue type

feature

DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.

3

Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.

1-2 days

Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.

stale

ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.

mostly clear

Prerequisites

Unicode grapheme clustersPythonTensorFlow

Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.

25

Research direction

The current training pipeline tokenizes transcripts using Unicode codepoints. The contributor should find the relevant tokenization code in the data preprocessing module (e.g., DeepSpeech.py or util.py) and modify it to segment text by grapheme clusters. Use a library like 'grapheme' or Python's 'unicodedata' to handle cluster boundaries. Ensure the change is backward compatible and test with multilingual datasets to verify correctness. Check issue comments for any additional discussion on implementation details.