monotonic-alignment-search
Monotonically align text and speech
Decision gist · record as of 2026-08-14
Yes, if you are building or extending a text-to-speech or speech alignment system and need a standalone, well-tested implementation of monotonic alignment search. The MIT license is permissive, install friction is moderate (compiled wheels available, PyTorch must be managed separately), and there are no known security vulnerabilities. However, maintenance is minimal (aging status, 303 days since last release); use it as a stable library component rather than expecting active development or rapid bug fixes.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- PyTorch must be installed separately; install via `uv add monotonic-alignment-search[cpu]` or `[cuda]` to include it, or install PyTorch manually first.
- Medium install friction due to compiled wheels; requires PyTorch to be installed separately (or via optional extras with uv).
- Last release 303 days ago with minimal maintenance activity (3 stars, aging status), but no active issues flagged.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use, modify, and distribute this package freely with minimal restrictions.
last release 2025-10-15 (303 days) · last repo commit 2025-10-15 · 3 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 131,042 downloads/mo, #11,612 on PyPI
Alternatives
Verify before relying
pip install monotonic-alignment-search
from monotonic_alignment_search import maximum_path
path = maximum_path(value, mask, implementation="cython")- Whether the package is actively maintained beyond the last commit date (2025-10-15) and whether bug reports are being addressed.
- Performance characteristics and alignment accuracy compared to alternative implementations or the original Glow-TTS repository.
- Whether the NumPy implementation is suitable for production use or primarily for prototyping.
What it is and what it does
Monotonic Alignment Search (MAS) is a specialized algorithm extracted from the Glow-TTS text-to-speech project that solves the problem of finding the optimal alignment between a text sequence and a speech sequence. It takes two tensors—a value matrix and a mask—and returns a path indicating which text tokens correspond to which speech frames, respecting the constraint that alignments must be monotonic (never backtrack in time). The package provides two implementations: a Cython-optimized version for performance and a pure NumPy fallback for compatibility.
The package is designed for researchers and developers working on speech synthesis, voice conversion, or other audio-text alignment tasks. It depends only on NumPy at runtime, though PyTorch is required to prepare the input tensors. The implementation is extracted directly from the original Glow-TTS repository and is intended for reuse in other projects that need this specific alignment algorithm.
Use it for
- Align text phonemes to speech frames in text-to-speech synthesis pipelines.
- Find frame-level correspondences between text and audio in voice conversion systems.
- Compute monotonic alignments for duration prediction models in speech generation.
- Prototype or extend speech synthesis models that require text-speech synchronization.
- Integrate alignment search into audio-text multimodal learning tasks.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or extending a text-to-speech or speech alignment system and need a standalone, well-tested implementation of monotonic alignment search.
The MIT license is permissive, install friction is moderate (compiled wheels available, PyTorch must be managed separately), and there are no known security vulnerabilities. However, maintenance is minimal (aging status, 303 days since last release); use it as a stable library component rather than expecting active development or rapid bug fixes.
Install
monotonic-alignment-search on PyPI
Before you install
Medium install friction due to compiled wheels; requires PyTorch to be installed separately (or via optional extras with uv). Last release 303 days ago with minimal maintenance activity (3 stars, aging status), but no active issues flagged.
PyTorch must be installed separately; install via `uv add monotonic-alignment-search[cpu]` or `[cuda]` to include it, or install PyTorch manually first.
License in practice
MIT license is permissive; you can use, modify, and distribute this package freely with minimal restrictions.
Quickstart
pip install monotonic-alignment-search
from monotonic_alignment_search import maximum_path
path = maximum_path(value, mask, implementation="cython")Verify before relying
- Whether the package is actively maintained beyond the last commit date (2025-10-15) and whether bug reports are being addressed.
- Performance characteristics and alignment accuracy compared to alternative implementations or the original Glow-TTS repository.
- Whether the NumPy implementation is suitable for production use or primarily for prototyping.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Aging 303 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 131,042 / month, #11,612 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Multimedia :: Sound/Audio :: SpeechTopic :: Software Development :: Libraries :: Python Modules |
Evidence: monotonic_alignment_search-0.2.1-cp310-cp310-macosx_11_0_arm64.whl; monotonic_alignment_search-0.2.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; monotonic_alignment_search-0.2.1-cp310-cp310-musllinux_1_2_x86_64.whl; monotonic_alignment_search-0.2.1-cp310-cp310-win_amd64.whl; monotonic_alignment_search-0.2.1-cp311-cp311-macosx_11_0_arm64.whl; monotonic_alignment_search-0.2.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; monotonic_alignment_search-0.2.1-cp311-cp311-musllinux_1_2_x86_64.whl; monotonic_alignment_search-0.2.1-cp311-cp311-win_amd64.whl; monotonic_alignment_search-0.2.1-cp312-cp312-macosx_11_0_arm64.whl; monotonic_alignment_search-0.2.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; monotonic_alignment_search-0.2.1-cp312-cp312-musllinux_1_2_x86_64.whl; monotonic_alignment_search-0.2.1-cp312-cp312-win_amd64.whl; monotonic_alignment_search-0.2.1-cp313-cp313-macosx_11_0_arm64.whl; monotonic_alignment_search-0.2.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; monotonic_alignment_search-0.2.1-cp313-cp313-musllinux_1_2_x86_64.whl; monotonic_alignment_search-0.2.1-cp313-cp313-win_amd64.whl; monotonic_alignment_search-0.2.1-cp314-cp314-macosx_11_0_arm64.whl; monotonic_alignment_search-0.2.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl; monotonic_alignment_search-0.2.1-cp314-cp314-musllinux_1_2_x86_64.whl; monotonic_alignment_search-0.2.1-cp314-cp314t-macosx_11_0_arm64.whl
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