Introduce cppjieba as a submodule for Chinese word segmentation by CrazySteve0605 · Pull Request #18548 · nvaccess/nvda

CrazySteve0605 · 2025-07-24T02:27:21Z

Introduce cppjieba, an NLP-based Chinese tokenizer, for implementing Chinese word navigation and braille output.

cppjieba is the C++ version of the popular Python library jieba, offering near-identical runtime performance.

A detialed integration analysis

1. Current State of Chinese Segmentation Tools

Chinese segmentation techniques trade accuracy for runtime and memory in predictable ways:

Dictionary-based (fast, lower OOV coverage). Libraries such as Jieba rely on prefix trees (tries) and greedy algorithms (maximum matching / DAG). These methods are CPU-efficient and lightweight but commonly miss new or domain-specific tokens (OOV words).
Statistical / sequence-labeling (better context, moderate cost). Approaches using HMMs, CRFs or perceptrons (adopted by tools like THULAC, LTP, pkuseg) label characters with B/I/E/S tags to model local context and transitions. They substantially improve OOV handling and achieve high F1 on news/text benchmarks, at the cost of higher computation and memory compared with pure dictionary methods.
Deep learning (highest accuracy, highest cost). Transformer/BERT-based models offer superior contextual understanding and segmentation accuracy, but their inference latency and memory footprint (often hundreds of megabytes to multiple gigabytes) make them unsuitable for real-time, low-latency assistive software like NVDA.

2. NVDA-Specific Requirements

NVDA requires low latency, a small memory footprint, and reliable offline operation — which rules out heavyweight deep-learning models. At the same time, very lightweight pure dictionary- or rule-based segmenters are also unsuitable: their lower accuracy and poor OOV handling lead to frequent mis-segmentation, inaccurate speech output, and increased user confusion in real-world documents. cppjieba therefore represents a pragmatic middle ground — native C++ performance and modest resource usage combined with a hybrid strategy (dictionary lookup plus HMM-based sequence labeling) that delivers appreciably better accuracy and OOV mitigation than pure dictionary methods, while remaining far lighter and faster than Transformer/BERT approaches — making it a sensible choice for improving Chinese text handling in NVDA without imposing large runtime or memory penalties.

Link to issue number:

Related to #4075 and a part of OSPP 2025 of NVDA.

Summary of the issue:

NVDA’s current word navigation mechanism relies on Unicode boundary rules through the Uniscribe API, which do not work well for languages such as Chinese due to the absence of explicit word delimiters.

Description of user facing changes:

None

Description of developer facing changes:

A tool to implement word navigation and braille output within Chinese content.

Description of development approach:

Added cppjieba as a submodule.
Added its wrapper and building script.

Testing strategy:

Confirm weather it can be successfully compiled and its segmentation function can be called by ctypes.

Known issues with pull request:

Code Review Checklist:

Documentation:
- Change log entry
- User Documentation
- Developer / Technical Documentation
- Context sensitive help for GUI changes
Testing:
- Unit tests
- System (end to end) tests
- Manual testing
UX of all users considered:
- Speech
- Braille
- Low Vision
- Different web browsers
- Localization in other languages / culture than English
API is compatible with existing add-ons.
Security precautions taken.

@coderabbitai summary

- Add `cppjieba` as a Git submodule under `third_party/cppjieba/` to provide robust Chinese word segmentation capabilities. - Update `.gitmodules` to point to the official `cppjieba` repository and configure it to track the `master` branch. - Update 'sconscript' to include the paths of 'cppjieba' and its dependency 'limonp' - Modify `copying.txt` to include the `cppjieba` license (MIT) alongside the project’s existing license, ensuring proper attribution and compliance. - Update documents

wmhn1872265132 · 2025-07-24T09:16:44Z

I downloaded the launcher built by GitHUB Actions for testing and it doesn't seem to work

cary-rowen · 2025-07-24T09:23:24Z

Imo, I suggest that initial development and debugging be carried out locally, especially during the stage when functionalities are not yet operational. If extensive testing by community early users is needed, at least new features should be functional.

CrazySteve0605 · 2025-07-24T09:28:34Z

I downloaded the launcher built by GitHUB Actions for testing and it doesn't seem to work

Apologies for the insufficient explanation. This PR is intended as an initial step of the overall work. It does not implement any segmentation functionality yet, but merely introduces the ‘cppjieba’ module. Therefore, it has no impact on end users.

CrazySteve0605 · 2025-07-24T09:39:42Z

Imo, I suggest that initial development and debugging be carried out locally, especially during the stage when functionalities are not yet operational. If extensive testing by community early users is needed, at least new features should be functional.

As many parts of the code need changes, splitting the work into smaller tasks might be more efficient, as the community can review them at the same time.

seanbudd · 2025-07-31T05:27:42Z

@CrazySteve0605 - can you please provide more information on why this library was selected over others? what were alternative options?

Co-authored-by: Sean Budd <seanbudd123@gmail.com>

- Introduce `JiebaSingleton` class in `cppjieba.hpp`/`cppjieba.cpp` with def file under nvdaHelper/cppjieba/' - Inherits from `cppjieba::Jieba` and exposes a thread-safe `getOffsets()` method - Implements Meyers’ singleton via `getInstance()` with a private constructor - Deletes copy constructor, copy assignment, move constructor, and move assignment to enforce single instance - Add C-style API in the same module: - `int initJieba()` to force singleton initialization - `int segmentOffsets(const char* text, int** charOffsets, int* outLen)` to perform segmentation and return character offsets - `void freeOffsets(int* ptr)` to release allocated offset buffer

- Change 'submodules' in 'jobs - buildNVDA - Build NVDA - Checkout NVDA' from 'true' to 'recursive' to ensure cppjieba's submodule is fetched. - This will cause the submodule of sonic to be fetched as well, which seems currently unused.

Co-authored-by: Sean Budd <seanbudd123@gmail.com>

seanbudd · 2025-08-15T06:43:43Z

@CrazySteve0605 - could you please update the PR description with what was requested in #18548 (comment), some more information on the module chosen?

Please also make sure to mark the PR as ready for review if it as this stage.

We are hoping to see implementation of segmentation with an example TextInfo such as WordDocumentTextInfo or Gecko_ia2_TextInfo

CrazySteve0605 · 2025-08-15T07:36:43Z

@seanbudd OK I see. I'm adding more details to make the main comment more informative. Instead of extending 'TextInfos', I'm creating a separate 'WordSegmentationStrategy' and 'WordSegmenter' that follow the strategy pattern, selecting an appropriate segmenter based on the Unicode fields present in the given text. I think this approach will be more extensible and easier to reuse in other potential components, such as braille output. I also plan to submit it as my next PR.

michaelDCurran · 2025-09-17T01:37:41Z

this pr is pretty much good. Just two small things in my last review.
We have decided that this and any other related PRs for this OSSP project will be merged into a special try-wordSegmentation-staging branch rather than master. So that all PRs can be reviewed and merged in to one working branch, which will then if successful, be merged to master all at the same time. Therefore I have switched the base branch of this pr to try-wordSegmentation-staging accordingly.

This reverts commit 06070c1.

Co-authored-by: Sean Budd <seanbudd123@gmail.com>

…ieba

michaelDCurran · 2025-09-29T02:13:14Z

Please note, that I incorrectly had merged this as a squash commit, which caused problems for dependent PRs such as #18735.
I have now reverted that squash commit and merged this PR's branch unsquashed as commit 093a825

…eText ### Link to issue number: blocked by #18548, closes #4075, related #16237 and [a part of OSPP 2025](https://summer-ospp.ac.cn/org/prodetail/25d3e0488?list=org&navpage=org) of NVDA. ### Summary of the issue: ### Description of user facing changes: Chinese text can be navigated by word via system caret or review cursor. ### Description of developer facing changes: ### Description of development approach: - [ ] update `textUtils` - [x] add `WordSegment` module - [x] create `WordSegmentationStrategy' as an abstract base class to select segmentation strategy based on text content, following Strategy Pattern - [x] implement `ChineseWordSegmentationStrategy` (for Chinese text) - [x] implement `UniscribeWordSegmentationStrategy` (for other languages as default strategy) - [x] update `textUtils/__init__.py` - [x] add `WordSegmenter` class for word segmentation, integrating segmentation strategies - [x] update `textInfos/offsets.py` - [x] replace `useUniscribe` with `useUniscribeForCharOffset` & `useWordSegmenterForWordOffset` for segmentation extensions - [x] integrate `WordSegmenter` for calculating word offsets - [ ] update document ### Testing strategy: ### Known issues with pull request: Word segmentation functionality was integrated in `OffsetsTextInfo`. In `OffsetsTextInfo`, word segmentation is based on Uniscribe by default and Unicode as a fall-back. Subclasses of OffsetsTextInfo #### Supported 1. `NVDAObjectTextInfo` 2. `InputCompositionTextInfo`: 3. `JABTextInfo` 4. `SimpleResultTextInfo` 5. `VirtualBufferTextInfo`: use self-hosted function to calculate offset and invoke iits superclass' `_getWordOffsets` #### Unsupported 1. `DisplayModelTextInfo`: straightly disable 2. `EditTextInfo`: straightly use Uniscribe 3. `ScintillaTextInfo`: entirely use self-defined 'word', for Scintilla-based editors such Notepad++ source/NVDAObjects/window/scintilla.py 4. `VsTextEditPaneTextInfo`: use a special COM automation API, for Microsoft Visual Studio and Microsoft SQL Server Management Studio source/appModules/devenv.py 5. `TextFrameTextInfo`: use self-defined 'word', based on PowerPoint's COM object, for PowerPoint's text frame source/appModules/powerpnt.py 6. `LwrTextInfo`: based on pre-computed words during related progress, for structured text using 'LineWordResult' (e.g. Windows OCR) source/contentRecog/__init__.py #### Partial Supported Some architectures totally or priorly use native difination of a 'word', which softwares depend on may not be able to use the new functionallity. 1. `IA2TextTextInfo`: override and fall back source/NVDAObjects/IAccessible/\_\_init\_\_.py ### Code Review Checklist:  - [ ] Documentation: - Change log entry - User Documentation - Developer / Technical Documentation - Context sensitive help for GUI changes - [ ] Testing: - Unit tests - System (end to end) tests - Manual testing - [ ] UX of all users considered: - Speech - Braille - Low Vision - Different web browsers - Localization in other languages / culture than English - [ ] API is compatible with existing add-ons. - [ ] Security precautions taken.

Squash commit of: - #18548 - #18735 - #18865 - #19324 - #19747 - #20041 - #20055 - #20106 - #20162 - #20178 - #20185 - #20205 - #20233 - #20242 - #20227 - #20279 - #20278 - #20288 Previous try branch commit history: #19166 --- This pull request introduces Chinese word segmentation support in NVDA through the integration of the `cppjieba` library. It adds the `cppjieba` submodule, builds and links the library into the NVDA build process, exposes new C++ and Python APIs for word segmentation, and updates braille and text handling to take advantage of improved segmentation for Chinese text. Configuration options and documentation are also updated to reflect the new dependency and features. **Integration of Chinese Word Segmentation (cppjieba):** * Added `cppjieba` as a submodule (`include/cppjieba`), included its license, and documented its usage and commit in the project documentation and `copying.txt`. [[1]](diffhunk://#diff-fe7afb5c9c916e521401d3fcfb4277d5071798c3baf83baf11d6071742823584R45-R47) [[2]](diffhunk://#diff-93d82d0c89b85c60d37ef8cb3828604e99efd8c53e20003a3214e8bbc715a638R1030) [[3]](diffhunk://#diff-3cb01a1174e7f0d6bcc2bee827d1f8df003c04469cea0fe88c5b4ac63aa06217R64-R70) [[4]](diffhunk://#diff-1728b4fa73cf927d66cd8f6fa2052dd1a7b33300e4f69e5a468761c3d4bd6390R100) * Implemented a SCons build script and build integration for `cppjieba`, ensuring the library and its dictionaries are built and installed as part of the NVDA build process. [[1]](diffhunk://#diff-94023871807359f67c40ba97760d6117d3e994483d29aa86e8d061bd8edadf21R1-R55) [[2]](diffhunk://#diff-a833c4b2ebcb5b6b4d112dee8dd790abd86a7cf30a463c1289c1adb7fc2a73ceR229-R232) [[3]](diffhunk://#diff-618cd5b83d62060ba3d027e314a21ceaf75d36067ff820db126642944145393eR52) * Added workflow improvements to ensure recursive submodule checkouts, so all dependencies (including nested ones) are fetched. **C++ and Python API Additions:** * Developed a thread-safe singleton wrapper and C API for `cppjieba` in `nvdaHelper/cppjieba`, exposing functions for initialization, segmentation, user word management, and memory management. [[1]](diffhunk://#diff-e445387d732c898ca23a1002fdd053848021a2c77ab71f870bbcc58f13cd6f53R1-R148) [[2]](diffhunk://#diff-af466fb9159a3862f17b7fc072d55c0024d413c73b2086cb922234953db6b7e0R1-R165) [[3]](diffhunk://#diff-14344d8042e55a42197012de94eeb0b8568c3ffb5e3a3876222e7cb1656a98daR1-R8) * Exposed new DLL and dictionary path properties in `NVDAState.py` for use by Python code. **Braille and Text Handling Enhancements:** * Updated braille output logic to use word segmentation for Chinese tables, applying a new `WordSegWithSeparatorOffsetConverter` to improve cursor and offset mapping. [[1]](diffhunk://#diff-56f1d6d0f5f57f0e55ce1ce5914c0ea1c66977dcd1d8f7d53d8da1d70eda41eeL79-R81) [[2]](diffhunk://#diff-56f1d6d0f5f57f0e55ce1ce5914c0ea1c66977dcd1d8f7d53d8da1d70eda41eeL609-R635) [[3]](diffhunk://#diff-56f1d6d0f5f57f0e55ce1ce5914c0ea1c66977dcd1d8f7d53d8da1d70eda41eeL632-R650) * Modified edit text handling to enforce the use of Uniscribe for character and word segmentation, ensuring consistent behavior with the new segmentation logic. [[1]](diffhunk://#diff-75bd009f6ff4404204bbbf144c81b729e6c24dcfbb16572b9b2df07b4f1c08eaR29) [[2]](diffhunk://#diff-75bd009f6ff4404204bbbf144c81b729e6c24dcfbb16572b9b2df07b4f1c08eaR167-R173) * Updated copyright and contributor attributions. [[1]](diffhunk://#diff-75bd009f6ff4404204bbbf144c81b729e6c24dcfbb16572b9b2df07b4f1c08eaL2-R2) [[2]](diffhunk://#diff-63eadb2c933d4403ec73ca9e97c4314a4f89ed9f3d8fde080bfc11315583d348L4-R5) **Configuration and Documentation Updates:** * Added configuration options for eager initialization and selection of word segmentation standards in `configSpec.py`. * Updated documentation to reflect the new dependency and its usage. [[1]](diffhunk://#diff-3cb01a1174e7f0d6bcc2bee827d1f8df003c04469cea0fe88c5b4ac63aa06217R64-R70) [[2]](diffhunk://#diff-1728b4fa73cf927d66cd8f6fa2052dd1a7b33300e4f69e5a468761c3d4bd6390R100) **Summary of Most Important Changes:** **1. Integration of cppjieba for Chinese Word Segmentation** - Added `cppjieba` as a submodule, updated `.gitmodules`, and documented its license and commit. [[1]](diffhunk://#diff-fe7afb5c9c916e521401d3fcfb4277d5071798c3baf83baf11d6071742823584R45-R47) [[2]](diffhunk://#diff-93d82d0c89b85c60d37ef8cb3828604e99efd8c53e20003a3214e8bbc715a638R1030) [[3]](diffhunk://#diff-3cb01a1174e7f0d6bcc2bee827d1f8df003c04469cea0fe88c5b4ac63aa06217R64-R70) [[4]](diffhunk://#diff-1728b4fa73cf927d66cd8f6fa2052dd1a7b33300e4f69e5a468761c3d4bd6390R100) - Implemented SCons build scripts and build integration for `cppjieba`, including dictionary installation. [[1]](diffhunk://#diff-94023871807359f67c40ba97760d6117d3e994483d29aa86e8d061bd8edadf21R1-R55) [[2]](diffhunk://#diff-a833c4b2ebcb5b6b4d112dee8dd790abd86a7cf30a463c1289c1adb7fc2a73ceR229-R232) [[3]](diffhunk://#diff-618cd5b83d62060ba3d027e314a21ceaf75d36067ff820db126642944145393eR52) - Improved workflow to fetch all submodules recursively. **2. C++/Python API and Library Exposure** - Created thread-safe singleton and C API for `cppjieba`, exposing segmentation and user word management functions. [[1]](diffhunk://#diff-e445387d732c898ca23a1002fdd053848021a2c77ab71f870bbcc58f13cd6f53R1-R148) [[2]](diffhunk://#diff-af466fb9159a3862f17b7fc072d55c0024d413c73b2086cb922234953db6b7e0R1-R165) [[3]](diffhunk://#diff-14344d8042e55a42197012de94eeb0b8568c3ffb5e3a3876222e7cb1656a98daR1-R8) - Exposed DLL and dictionary paths in `NVDAState.py` for use by Python code. **3. Braille and Text Handling Improvements** - Enhanced braille output to use word segmentation for Chinese, improving offset and cursor mapping. [[1]](diffhunk://#diff-56f1d6d0f5f57f0e55ce1ce5914c0ea1c66977dcd1d8f7d53d8da1d70eda41eeL79-R81) [[2]](diffhunk://#diff-56f1d6d0f5f57f0e55ce1ce5914c0ea1c66977dcd1d8f7d53d8da1d70eda41eeL609-R635) [[3]](diffhunk://#diff-56f1d6d0f5f57f0e55ce1ce5914c0ea1c66977dcd1d8f7d53d8da1d70eda41eeL632-R650) - Updated edit text handling to enforce Uniscribe for segmentation. [[1]](diffhunk://#diff-75bd009f6ff4404204bbbf144c81b729e6c24dcfbb16572b9b2df07b4f1c08eaR29) [[2]](diffhunk://#diff-75bd009f6ff4404204bbbf144c81b729e6c24dcfbb16572b9b2df07b4f1c08eaR167-R173) **4. Configuration and Documentation** - Added configuration options for word segmentation initialization and standards. - Updated documentation and copyright attributions. [[1]](diffhunk://#diff-3cb01a1174e7f0d6bcc2bee827d1f8df003c04469cea0fe88c5b4ac63aa06217R64-R70) [[2]](diffhunk://#diff-75bd009f6ff4404204bbbf144c81b729e6c24dcfbb16572b9b2df07b4f1c08eaL2-R2) [[3]](diffhunk://#diff-63eadb2c933d4403ec73ca9e97c4314a4f89ed9f3d8fde080bfc11315583d348L4-R5) This lays the groundwork for robust Chinese word navigation and segmentation in NVDA, improving accessibility for Chinese users.

seanbudd requested a review from michaelDCurran July 24, 2025 02:29

CrazySteve0605 added 2 commits July 24, 2025 16:51

Update what's new

fb4efef

Add comments for building script of cppjieba and its dependency

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CrazySteve0605 marked this pull request as ready for review July 24, 2025 09:05

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CrazySteve0605 and others added 3 commits August 1, 2025 13:04

Update projectDocs/dev/createDevEnvironment.md

06070c1

Co-authored-by: Sean Budd <seanbudd123@gmail.com>

Update include/readme.md

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Co-authored-by: Sean Budd <seanbudd123@gmail.com>

Remove changes in sconscript for localLIb

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CrazySteve0605 marked this pull request as draft August 4, 2025 00:32

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add building script for cppjieba

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Merge branch 'master' into integrateCPPJieba

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Merge branch 'master' into integrateCPPJieba

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Update .gitignore for cppjieba

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Update building and setup script for cppjieba's dicts installation

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CrazySteve0605 and others added 2 commits August 9, 2025 20:30

update copyright headers based on @seanbudd's suggestions

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Update include/readme.md

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Co-authored-by: Sean Budd <seanbudd123@gmail.com>

CrazySteve0605 marked this pull request as ready for review September 12, 2025 11:10

michaelDCurran requested changes Sep 17, 2025

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michaelDCurran changed the base branch from master to try-chineseWordSegmentation-staging September 17, 2025 01:33

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CrazySteve0605 mentioned this pull request Sep 18, 2025

Add Word Separaters in Braille Output for Chinese text #18865

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CrazySteve0605 added 3 commits September 20, 2025 23:53

Merge branch 'master' into integrateCPPJieba

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Revert "Update projectDocs/dev/createDevEnvironment.md"

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This reverts commit 06070c1.

avoid using compilation time path

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Update .gitattributes

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Merge branch 'try-chineseWordSegmentation-staging' into integrateCPPJ…

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…ieba

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Merge branch 'try-chineseWordSegmentation-staging' into integrateCPPJ…

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…ieba

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seanbudd mentioned this pull request Nov 5, 2025

[WIP] Merge Chinese Word Segmentation work #19166

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CrazySteve0605 deleted the integrateCPPJieba branch May 18, 2026 02:59

seanbudd mentioned this pull request May 20, 2026

Add Chinese Word Segmentation #20183

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LeonarddeR mentioned this pull request Jun 15, 2026

Word navigation shortcomings in Browse mode ICU can fix #20343

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CrazySteve0605 commented Jul 24, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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A detialed integration analysis

1. Current State of Chinese Segmentation Tools

2. NVDA-Specific Requirements

Link to issue number:

Summary of the issue:

Description of user facing changes:

Description of developer facing changes:

Description of development approach:

Testing strategy:

Known issues with pull request:

Code Review Checklist:

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CrazySteve0605 commented Jul 24, 2025 •

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