---
id: ko-speech-tools
version: "0.1.0"
license: Apache-2.0
license_treatment: permissive
maintenance: aging
---

# ko-speech-tools — Korean speech/NLP tools

License: permissive · Maintenance: aging · Downloads: 103.2K/mo

## What it is and what it does

Korean Speech Tools is a collection of utilities for processing Korean language text and speech. It bundles three main capabilities: converting Hangul (Korean script) to romanized Latin characters, decomposing and recomposing Hangul into Jamo (individual character components), and converting written Korean text to phonetic pronunciation for speech synthesis. The package consolidates previously unmaintained libraries and removes unnecessary external dependencies from the core functionality.

The core romanization and Jamo tools have no external dependencies and work with modern Python versions (3.10+). Grapheme-to-phoneme conversion is available as an optional extra that requires the mecab-ko morphological analyzer. This is useful for developers building Korean speech synthesis systems, linguistic analysis tools, or text processing pipelines that need to work with Korean script in different representations.

Use it for:

- Convert Korean text to romanized Latin script for display or input systems that don't support Hangul.
- Decompose Korean characters into individual Jamo components for linguistic analysis or custom text processing.
- Generate phonetic pronunciations from written Korean text for text-to-speech synthesis systems.
- Build Korean language NLP pipelines that need to normalize or transform Korean script representations.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Korean language processing tools including Hangul romanization, Jamo character conversion, and grapheme-to-phoneme conversion for speech synthesis.

Yes, if you need Korean language processing tools and can accept alpha-stage software. The package has low install friction, no core dependencies, and permissive licensing. However, verify that the G2P accuracy meets your speech synthesis requirements and understand that maintenance is uncertain given the recent release and small repository activity. Not recommended for production systems requiring long-term support guarantees.

## Install

pip install ko-speech-tools
uv add ko-speech-tools
poetry add ko-speech-tools

## Installing ko-speech-tools

Before you install: Low install friction with no core dependencies; optional G2P functionality requires mecab-ko. Package is in alpha status and was first released recently, so treat as early-stage.

License in practice: Apache-2.0 permissive license allows commercial and private use. Package combines code from multiple sources (g2pkk, hangul_romanize, jamo, tacotron) each under their original licenses (Apache-2.0, BSD-2-Clause, MIT); individual files document their respective licenses.

Quickstart:

pip install ko-speech-tools

from ko_speech_tools import hangul_romanize
print(hangul_romanize("물엿"))  # Output: 'mul-yeos'

from ko_speech_tools.jamo import h2j, j2hcj
print(h2j('한굴'))  # Hangul to Jamo conversion

Requires Python 3.10 or later. G2P functionality requires optional mecab-ko dependency (install with: pip install ko-speech-tools[g2p]).

Verify before relying:

- Whether G2P accuracy and performance are suitable for production speech synthesis pipelines.
- Maintenance roadmap and whether the package will receive updates beyond its current alpha state.
- Compatibility with non-Latin romanization standards or alternative Jamo representations.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 103.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

korean language processing, hangul romanization, jamo conversion, grapheme to phoneme korean, korean speech synthesis, korean nlp tools, korean text processing, korean-nlp, speech-synthesis, text-processing

[View on SkillFed](https://skillfed.io/packages/ko-speech-tools) · [View on PyPI](https://pypi.org/project/ko-speech-tools/)