k2-fsa/sherpa-onnx
Jan 2026 – Jan 2026
1 Month active
Languages Used
C++Python
Technical Skills
C++ developmentPython scriptingmachine learningtext-to-speech
pqsworld
PROFILE
Pqsworld
Worked on the sherpa-onnx repository to enhance the MeloTTS English text-to-speech workflow by addressing a pronunciation inconsistency. Focused on stability and accuracy, the developer delivered a targeted bug fix in C++ that unified the token IDs for uppercase and lowercase 'V' and 'v', ensuring consistent pronunciation in TTS output. This change improved the naturalness of English speech synthesis and reduced ambiguity in downstream multilingual processing. The work involved C++ source debugging, tokenization logic, and patch management, demonstrating skills in both C++ and Python. The fix contributed to more reliable user-facing output and streamlined quality assurance processes.
Overall Statistics
Feature vs Bugs
0%Features
Repository Contributions
1Total
Bugs
1
Commits
1
Features
0
Lines of code
11
Activity Months1
Your Network
38 peopleShared Repositories
38
Work History
January 2026
1 Commits
Jan 1, 2026January 2026 monthly summary for k2-fsa/sherpa-onnx. Focus: stability and pronunciation accuracy in MeloTTS within the sherpa-onnx workflow. Delivered a targeted bug fix to unify token IDs for V and v in the MeloTTS English model, improving pronunciation consistency in TTS output. Impact: More natural English MeloTTS output, fewer mispronunciations, and more reliable downstream processing for multilingual pipelines. The fix is implemented in csrc/melotts and committed as 3c60c609a2cc9871b118fe98f833c3b77758eb2b (#3002). Technologies/skills demonstrated: C/C++ source debugging, tokenization/token-id mapping, patch management, code review, and TTS model integration. Business value: Enhanced user-facing quality, reduced QA cycles, and lower support costs due to more consistent pronunciation across uppercase/lowercase tokens.
1 Commits
Jan 1, 2026January 2026 monthly summary for k2-fsa/sherpa-onnx. Focus: stability and pronunciation accuracy in MeloTTS within the sherpa-onnx workflow. Delivered a targeted bug fix to unify token IDs for V and v in the MeloTTS English model, improving pronunciation consistency in TTS output. Impact: More natural English MeloTTS output, fewer mispronunciations, and more reliable downstream processing for multilingual pipelines. The fix is implemented in csrc/melotts and committed as 3c60c609a2cc9871b118fe98f833c3b77758eb2b (#3002). Technologies/skills demonstrated: C/C++ source debugging, tokenization/token-id mapping, patch management, code review, and TTS model integration. Business value: Enhanced user-facing quality, reduced QA cycles, and lower support costs due to more consistent pronunciation across uppercase/lowercase tokens.
January 2026
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++Python
Technical Skills
C++ developmentPython scriptingmachine learningtext-to-speech
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline