wetext 0.1.2

WeTextProcessing Runtime

WeTextProcessing Runtime

Python runtime for WeTextProcessing (does not depend on Pynini).

WeTextProcessing is a text processing library that provides text normalization (TN) and inverse text normalization (ITN) capabilities for Chinese, English and Japanese text. It uses Finite State Transducers (FSTs) for efficient text processing.

Features

• Text Normalization (TN) for Chinese, English and Japanese
• Inverse Text Normalization (ITN) for Chinese and Japanese
• Traditional to Simplified Chinese conversion
• Full-width to Half-width character conversion
• Interjection removal
• Punctuation removal
• Out-of-vocabulary (OOV) word tagging
• Erhua removal (for Chinese)
• 0-to-9 conversion (for Chinese and Japanese ITN)

Installation

pip install wetext

Usage

Python API

Text Normalization (TN)

from wetext import Normalizer

# Chinese TN with erhua removal
normalizer = Normalizer(lang="zh", operator="tn", remove_erhua=True)
result = normalizer.normalize("你好 WeTextProcessing 1.0，全新版本儿，简直666")
print(result)  # 你好 WeTextProcessing 一点零，全新版本，简直六六六

# English TN
normalizer = Normalizer(lang="en", operator="tn")
result = normalizer.normalize("Today is August 8, 2024.")
print(result)  # Today is the eighth of august , twenty twenty four.

Inverse Text Normalization (ITN)

from wetext import Normalizer

# Chinese ITN
normalizer = Normalizer(lang="zh", operator="itn", enable_0_to_9=False)
result = normalizer.normalize("你好 WeTextProcessing 一点零，全新版本儿，简直六六六，九和六")
print(result)  # 你好 WeTextProcessing 1.0，全新版本儿，简直666，九和六

Command Line Interface

# Basic usage
wetext "你好 WeTextProcessing 1.0，全新版本儿，简直666"

# With options
wetext --lang zh --operator tn --remove-erhua "你好 WeTextProcessing 1.0，全新版本儿，简直666"

# Convert traditional to simplified Chinese
wetext --traditional-to-simple "你好，這是測試。"

# Remove punctuations
wetext --remove-puncts "你好，這是測試。"

API Reference

Normalizer Class

Normalizer(
    lang: Literal["auto", "en", "zh", "ja"] = "auto",
    operator: Literal["tn", "itn"] = "tn",
    traditional_to_simple: bool = False,
    full_to_half: bool = False,
    remove_interjections: bool = False,
    remove_puncts: bool = False,
    tag_oov: bool = False,
    enable_0_to_9: bool = False,
    remove_erhua: bool = False,
)

Parameters

• lang: The language of the text. Can be "auto", "en", "zh" or "ja". Default is "auto".
• operator: The operator to use. Can be "tn" (text normalization) or "itn" (inverse text normalization). Default is "tn".
• traditional_to_simple: Whether to convert traditional Chinese to simplified Chinese. Default is False.
• full_to_half: Whether to convert full-width characters to half-width characters. Default is False.
• remove_interjections: Whether to remove interjections. Default is False.
• remove_puncts: Whether to remove punctuation. Default is False.
• tag_oov: Whether to tag out-of-vocabulary words. Default is False.
• enable_0_to_9: Whether to enable 0-to-9 conversion for ITN. Default is False.
• remove_erhua: Whether to remove erhua for TN. Default is False.

Methods

• normalize(text: str, lang: Optional[Literal["auto", "en", "zh", "ja"]] = None) -> str: Normalize the text.

CLI Options

• --lang, -l: Set the language. Choices are "auto", "en", "zh", "ja". Default is "auto".
• --operator, -o: Set the operator. Choices are "tn", "itn". Default is "tn".
• --traditional-to-simple: Convert traditional Chinese to simplified Chinese.
• --full-to-half: Convert full-width characters to half-width characters.
• --remove-interjections: Remove interjections.
• --remove-puncts: Remove punctuation.
• --tag-oov: Tag out-of-vocabulary words.
• --enable-0-to-9: Enable 0-to-9 conversion.
• --remove-erhua: Remove erhua.

License

Apache License 2.0