asrbench 0.1.0

Extensible, easy to use Python framework for evaluation of audio transcription systems.

:brazil: Versão Português Brasileiro

ASRBench

Evaluate, compare and find the best model for audio transcription.

Index

• ASRBench
  • Evaluate, compare and find the best model for audio transcription.
  • Index
  • Introduction
  • Installation
  • Usage
  • Contribution
  • About
  • License

Introduction

ASRBench is a framework developed in Python to create and run benchmarks of audio transcription systems. It allows researchers and developers to compare different transcription systems in terms of accuracy, performance and resource utilization.

Installation

To install ASRBench, all you need is Python 3.12+ and pip. Use the command below to install the latest version:

pip install asrbench

Usage

ASRBench allows you to configure and run the benchmark using a YAML configuration file. This approach facilitates the benchmark environment by allowing the user to define datasets, transcribers and output parameters in a simple and declarative way. parameters in a simple and declarative way. For more details on the structure of the configuration file, go to documentation.

Below is an example of the configuration file structure:

# data output configuration
output:
  type: "csv"
  dir: "./results"
  filename: "example_filename"

# configuration of datasets
datasets:
  dataset1:
    audio_dir: "resources/common_voice_05/wav"
    reference_dir: "resources/common_voice_05/txt"

# transcription system configuration
transcribers:
  faster_whisper_medium_int8:
    asr: "faster_whisper"
    model: "medium"
    compute_type: "int8"
    device: "cpu"
    beam_size: 5
    language: "en"  

With the configuration file ready, just create a Python script to read the file and set up the benchmark environment. See an example below:

from asrbench.config_loader import ConfigLoader

loader = ConfigLoader("path/to/configfile.yml")
benchmark = loader.set_up_benchmark()
benchmark.run()

If you also want to generate a PDF report from the data generated in the benchmark, just add the following code snippet:

from asrbench.report.report_template import DefaultReport
from asrbench.report.input_ import CsvInput
...

output_path = benchmark.run()
report = DefaultReport(CsvInput(output_filepath))
report.generate_report()

If you prefer a more direct and simplified solution, you can check out asrbench-cli.

Contribution

If you want to contribute to ASRBench, see CONTRIBUTING.md for information on how to set up the development environment and the necessary dependencies. The main development tools are defined in the file pyproject.toml and are managed with Poetry.

About

ASRBench was developed as part of a course completion project to explore and evaluate the efficiency of audio transcription models. of audio transcription models. The academic project provides a detailed analysis of the framework's development, as well as the challenges and results obtained during the research. For more information, see TCC.

License

Distributed under the MIT license. See the LICENSE file for more details.

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