README.md

metadata

license: mit
language:
  - zh
  - en
tags:
  - audio
  - speech-alignment
  - wav2vec2
  - ctc
  - forced-alignment

🌊 FlexAligner: Robust Speech-Text Alignment Framework

FlexAligner is a robust two-stage speech-text alignment framework designed specifically for "non-ideal" real-world acoustic data. FlexAligner 是一种强鲁棒性的两阶段语音-文本对齐框架，专门为“非理想”的真实世界语音数据设计。

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🌟 Key Features / 核心功能

English

• Robustness to Mismatched Data: Unlike traditional MFA (Montreal Forced Aligner), FlexAligner automatically identifies and skips mismatched segments (e.g., laughter, background noise, or un-transcribed words), preventing cumulative errors.
• Two-Stage Architecture:
  1. Stage 1 (CTC Chunking): Macro-segmentation to locate reliable "speech islands."
  2. Stage 2 (CE Alignment): Micro-alignment using dynamic hop calibration for sub-millisecond boundary regression.
• Eliminating Temporal Drift: Includes a self-calibrating decoding algorithm for long recordings, ensuring phoneme boundaries at the end of the file remain strictly aligned with samples.

中文

• 处理不匹配数据：不同于传统的 MFA (Montreal Forced Aligner)，FlexAligner 能够自动识别并跳过音频与文本不匹配的部分（如笑声、长时间噪音或漏记的单词），而不会产生累积误差。
• 两阶段对齐架构：
  1. Stage 1 (CTC Chunking): 宏观切分，定位可靠的语音“岛屿”。
  2. Stage 2 (CE Alignment): 微观对齐，利用动态步长校准实现亚毫秒级的边界回归。
• 消除时间漂移：针对长音频设计了自校准解码算法，确保音频末尾的音素边界依然能够与采样点严格对齐。

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📦 Model Components / 模型组成

This repository contains the weights for the two core components of FlexAligner: 本仓库包含 FlexAligner 运行所需的两套核心权重：

• hf_phs/: Wav2Vec 2.0 based CTC chunking model. / 基于 Wav2Vec 2.0 训练的 CTC 切分模型。
• ce2/: High-precision frame-level Cross-Entropy alignment model. / 高精度帧级别交叉熵对齐模型。

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🚀 Quick Start / 快速上手

CLI Usage / 命令行使用

After installation, you can call the cloud models directly via the CLI: 安装后，你可以通过 CLI 命令行直接调用云端模型：

flex-align input.wav transcript.txt --dynamic -o output.TextGrid

Python API Or integrate it into your Python pipeline: / 或者在 Python 代码中集成：

from flexaligner import FlexAligner

# Use the Hugging Face Repo ID to automatically download and load weights
# 填入本仓库 ID，程序会自动处理模型下载与加载
aligner = FlexAligner(config={
    "chunk_model_path": "USTCPhonetics/FlexAligner",
    "use_dynamic_hop": True
})

aligner.align("test.wav", "test.txt", "result.TextGrid")

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📜 License / 协议 This project is licensed under the MIT License. Feel free to use it in academic research or commercial projects. 本项目遵循 MIT License。你可以自由地在学术研究或商业项目中使用。

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