bewer 0.1.0a4

Evaluation and analysis framework for automatic speech recognition in Python.

BeWER

Beyond Word Error Rate → BeWER (/ˈbiːvər/) 🦫

Note: This project is not production ready and is still in early development.

BeWER is an evaluation and analysis framework for automatic speech recognition in Python. It defines a transparent YAML-based approach for configuring evaluation pipelines and makes it easy to inspect and analyze individual examples through a web-based interface. The built-in preprocessing pipeline and metrics collection are designed to cover all conventional use cases and then some, while still being fully extensible.

Contents | Installation | Quickstart |

Installation

pip install bewer

Quickstart

Create a Dataset

from bewer.core import Dataset

dataset = Dataset()

Add data

From a file:

dataset.load_csv(
    "data.csv",
    ref_col="reference",
    hyp_col="hypothesis",
)

Or manually:

for reference, hypothesis in iterator:
    dataset.add(ref=ref, hyp=hyp)

List available metrics

dataset.metrics.list_metrics()

Compute metrics lazily

print(f"WER: {dataset.metrics.wer.value:.4f}")