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Command-line interface to evaluate text-to-speech mean opinion score studies done on Amazon Mechanical Turk.

Project description

tts-mos-test-mturk

PyPI PyPI MIT PyPI PyPI PyPI DOI

Command-line interface (CLI) to evaluate text-to-speech (TTS) mean opinion score (MOS) studies done on Amazon Mechanical Turk (MTurk).

Features

  • init: initialize project from .json-file
  • masks
    • create: create empty mask
    • mask-workers-by-id: mask workers by their WorkerId
    • mask-workers-by-age-group: mask workers by their age group
    • mask-workers-by-gender: mask workers by their gender
    • mask-workers-by-assignments-count: mask workers by their count of assignments
    • mask-workers-by-masked-ratings-count: mask workers by their count of masked ratings
    • mask-workers-by-correlation: mask workers by their algorithm/sentence correlation
    • mask-workers-by-correlation-percent: mask workers by their algorithm/sentence correlation (percentage-wise)
    • mask-assignments-by-id: mask assignments by their AssignmentId
    • mask-assignments-by-device: mask assignments by their listening device
    • mask-assignments-by-status: mask assignments by their status
    • mask-assignments-by-time: mask assignments by their submit time
    • mask-rating-outliers: mask outlying ratings
    • merge-masks: merge masks together
    • reverse-mask: reverse mask
  • stats
    • print-mos: print MOS and CI95
    • print-masking-stats: print masking statistics
    • print-worker-stats: print worker statistics for each algorithm
    • print-assignment-stats: print assignment statistics for each worker
    • print-sentence-stats: print sentence statistics for each algorithm
    • print-data: print all data points
  • mturk
    • prepare-approval: generate approval file
    • prepare-rejection: generate rejection file
    • prepare-bonus-payment: generate bonus payment file

Installation

pip install tts-mos-test-mturk --user

Usage

usage: mos-cli [-h] [-v] {init,masks,stats,mturk} ...

CLI to evaluate text-to-speech MOS studies done on MTurk.

positional arguments:
  {init,masks,stats,mturk}
                                        description
    init                                initialize project from .json-file
    masks                               masks commands
    stats                               stats commands
    mturk                               mturk commands

options:
  -h, --help                            show this help message and exit
  -v, --version                         show program's version number and exit

Project JSON example

{
  "algorithms": [
    "alg1",
    "alg2",
    "alg3",
    "alg4"
  ],
  "files": [
    "file1",
    "file2",
    "file3"
  ],
  "workers": {
    "worker1": {
      "gender": "male",
      "age_group": "18-29",
      "assignments": {
        "assignment1": {
          "device": "headphone",
          "state": "Approved",
          "hit": "hit1",
          "time": "13.07.23 05:08:04",
          "ratings": [
            {
              "algorithm": "alg1",
              "file": "file1",
              "votes": {
                "naturalness": 3,
                "intelligibility": 5
              }
            },
            {
              "algorithm": "alg2",
              "file": "file3",
              "votes": {
                "naturalness": 2,
                "intelligibility": 4
              }
            }
          ]
        }
      }
    }
  }
}

For a longer example see etc/example.json. It contains 4 algorithms and 120 files which were rated by 36 dummy workers in batches of 10 files per assignment. An example parsing of that file is under etc/example.sh.

Roadmap

  • add masks mask-assignments-not-of-last-month/week/day
  • make device, state, hit and time optional
  • make tax value optional

Dependencies

  • numpy
  • pandas
  • tqdm
  • ordered-set>=4.1.0
  • mean-opinion-score==0.0.2

Contributing

If you notice an error, please don't hesitate to open an issue.

Development setup

# update
sudo apt update
# install Python 3.8, 3.9, 3.10 & 3.11 for ensuring that tests can be run
sudo apt install python3-pip \
  python3.8 python3.8-dev python3.8-distutils python3.8-venv \
  python3.9 python3.9-dev python3.9-distutils python3.9-venv \
  python3.10 python3.10-dev python3.10-distutils python3.10-venv \
  python3.11 python3.11-dev python3.11-distutils python3.11-venv
# install pipenv for creation of virtual environments
python3.8 -m pip install pipenv --user

# check out repo
git clone https://github.com/stefantaubert/tts-mos-test-mturk.git
cd tts-mos-test-mturk
# create virtual environment
python3.8 -m pipenv install --dev

Running the tests

# first install the tool like in "Development setup"
# then, navigate into the directory of the repo (if not already done)
cd tts-mos-test-mturk
# activate environment
python3.8 -m pipenv shell
# run tests
tox

Final lines of test result output:

  py38: commands succeeded
  py39: commands succeeded
  py310: commands succeeded
  py311: commands succeeded
  congratulations :)

License

MIT License

Acknowledgments

  • Ribeiro, F., Florêncio, D., Zhang, C., & Seltzer, M. (2011). CrowdMOS: An approach for crowdsourcing mean opinion score studies. 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2416–2419. https://doi.org/10.1109/ICASSP.2011.5946971

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 416228727 – CRC 1410

Citation

If you want to cite this repo, you can use this BibTeX-entry generated by GitHub (see About => Cite this repository).

Taubert, S. (2024). tts-mos-test-mturk (Version 0.0.2) [Computer software]. https://doi.org/10.5281/zenodo.10461539

Changelog

  • v0.0.2 (2024-01-05)
    • Bugfix:
      • mask mask-workers-by-correlation-percent: sorting was not always correct
    • Added:
      • mask mask-workers-by-correlation-percent: added option to include masked workers in percentage calculation
      • mturk prepare-bonus-payment: added logging of fees for Mechanical Turk
      • mturk prepare-approval: added logging of fees for Mechanical Turk
      • added mask mask-assignments-by-status
      • added mask mask-assignments-by-time
      • added parsing of HITId
      • added option to mask assignments before preparing rejection CSV
      • added ! before mask name reverses mask on input
      • added masks mask-assignments-by-id
      • added masks mask-workers-by-id
    • Changed:
      • moved template creation and preparation to another repository
      • removed worktime parsing
  • v0.0.1 (2023-02-23)
    • Initial release

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