texterrors

library1.1.8pypypi✓ verified 86d ago

texterrors is a Python library and command-line tool designed to score ASR (Automatic Speech Recognition) or transcription output against a reference. It provides metrics such as Word Error Rate (WER) and Character Error Rate (CER), supports standard and character-aware alignment, generates detailed error reports, and can produce colored output for inspection. The library also features comparison of multiple hypothesis files, per-group metrics (e.g., per-speaker WER), keyword and OOV (Out-Of-Vocabulary) evaluation, oracle WER, and simple entity accuracy. It aims to be an easy-to-use, modify, and extend alternative to older tools like `sclite`. The current version is 1.1.6, and it receives active maintenance and frequent updates.

data testing ai-ml

pip install texterrors

github ↗package ↗

INSTALL

IMPORT

SIG · TEXTERRORS

texterrors

datapythonv1.1.8

Install

7.2s avg

Import

666ms

Disk

127MB

Pass rate

8/ 10

Env Coverage8 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.1.8 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

✓ —

✓ 7.5s

py 3.11

✓ —

✓ 6.53s

py 3.12

✓ —

✓ 5.78s

py 3.13

✕ build_error

py 3.9

✓ —

✓ 8.83s

127MB installed

● package 127MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

align_texts

✓ from texterrors import align_texts

This is the primary function for programmatic text alignment and error rate calculation.

This quickstart demonstrates how to use the `align_texts` function to calculate WER and CER programmatically. It takes tokenized reference and hypothesis lists and returns a detailed JSON object with various metrics. For more complex features such as colored output, per-group analysis, or simple entity accuracy, the `texterrors` command-line tool is often more convenient and directly supported.

from texterrors import align_texts # Reference and hypothesis texts as lists of tokens reference_tokens = ["this", "is", "a", "test", "sentence"] hypothesis_tokens = ["this", "is", "test", "sentance"] # Perform alignment and get metrics # The return_detailed_json=True flag provides comprehensive results. # For full features (like colored output, group metrics, entity accuracy), # the command-line interface is often more direct. result = align_texts( reference_tokens, hypothesis_tokens, ref_id="ref_utt_1", # Optional: utterance ID hyp_id="hyp_utt_1", # Optional: utterance ID return_detailed_json=True # Get comprehensive results ) print(f"WER: {result['wer']:.2f}%") print(f"CER: {result['cer']:.2f}%") print(f"Substitutions: {result['substitutions']}") print(f"Deletions: {result['deletions']}") print(f"Insertions: {result['ins']}") print("\nFirst 10 alignment details (token level):") for item in result['aligned_tokens'][:10]: print(item)

texterrors --version

Debug

Known issues

breakingThe `weighted WER` feature was removed, and `simple entity accuracy` was introduced in its place. Code relying on `weighted WER` will break.

fix

Migrate any usage of `weighted WER` to use the new `simple entity accuracy` features if applicable, or remove the deprecated functionality.

affects: <1.1.6

breakingThe extension module (handling core performance-critical parts) was migrated from `pybind11` to `nanobind` and the build system moved to `CMake/scikit-build-core`. This primarily affects users building `texterrors` from source or in complex C++/Python environments.

fix

Ensure your development environment has `nanobind` and `CMake` properly configured if building from source. For most users installing via `pip install texterrors`, pre-built wheels should handle this transparently.

affects: <1.1.6

gotchaCharacter-aware alignment, while a powerful feature, can result in a slightly higher WER compared to traditional tools (e.g., Kaldi's `sclite`) due to its more granular alignment strategy. Since 22.06.22, character-aware alignment is *off* by default.

fix

Be aware of this difference when comparing results. If precise parity with traditional tools is required, ensure character-aware alignment is explicitly disabled, or understand the implications if it's enabled.

affects: All versions

gotchaWhen using the command-line tool's colored output (`-c` flag), the output should be viewed with a pager like `less -R` to correctly interpret ANSI escape codes and display colors.

fix

Pipe the output to `less -R` (e.g., `texterrors -c ref.txt hyp.txt | less -R`).

affects: All versions

gotchaThe command-line tool expects specific input file formats. For files where each line starts with an utterance ID, the `--isark` flag is required. For CTM-like input including timing fields, `--isctm` is needed.

fix

Always check the `--help` output for the correct input flags (`texterrors -h`) and use them as appropriate for your data format.

affects: All versions

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'texterrors'

The `texterrors` package has not been installed in the current Python environment.

fix

pip install texterrors

ValueError: Reference and hypothesis files must have the same number of lines.

The input reference and hypothesis text files contain a different number of lines, preventing a one-to-one comparison for each utterance.

fix

Ensure both `reference_file` and `hypothesis_file` have the exact same number of lines, corresponding to each utterance pair.

TypeError: 'str' object is not iterable

The `texterrors.wer` and `texterrors.compute` functions expect `list[str]` (a list of lines) for their reference and hypothesis arguments, but received single `str` objects instead.

fix

Pass the reference and hypothesis as lists containing the strings, even for a single utterance: `texterrors.wer(["hello world"], ["hallo world"])`.

unrecognized arguments: --some_invalid_arg

The command-line interface was invoked with an argument that is not recognized or supported by the `texterrors` tool or its current version.

fix

Consult `texterrors --help` or the documentation for available arguments and correct spelling.

UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe4 in position ...

The input reference or hypothesis file is not encoded in UTF-8, but `texterrors` attempts to read it using the default UTF-8 encoding.

fix

Specify the correct encoding using the `--encoding` argument in the command-line tool, e.g., `texterrors --encoding latin-1 ref.txt hyp.txt`.

Upgrade

Version history

1.1.8latest on PyPI · released Jun 9, 2026

Audit

Dependencies

pythonrequiredRequired Python version.

regexrequiredA dependency for advanced regular expression operations, which was explicitly fixed in a past release.

Agent activity

23 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/RuABraun/texterrors ↗

packagehttps://pypi.org/project/texterrors/ ↗