update description

CITATION.cff

@@ -1,6 +1,6 @@
 cff-version: 1.2.0
 title: mean-opinion-score
-abstract: Command-line interface and Python library to evaluate text-to-speech mean opinion score studies done on Amazon Mechanical Turk.
+abstract: Library for calculating the mean opinion score and 95% confidence interval of the standard deviation of text-to-speech ratings according to Ribeiro et al. (2011).
 message: >-
   If you use this software, please cite it using the
   metadata from this file.
@@ -16,4 +16,4 @@ version: 0.0.1
 date-released: 2023-02-23
 license: MIT
 url: https://github.com/stefantaubert/mean-opinion-score
-doi: 10.5281/zenodo.7669641
+doi: 10.5281/zenodo.7670649

README.md

@@ -6,10 +6,9 @@
 [![PyPI](https://img.shields.io/pypi/wheel/mean-opinion-score.svg)](https://pypi.python.org/pypi/mean-opinion-score/#files)
 ![PyPI](https://img.shields.io/pypi/implementation/mean-opinion-score.svg)
 [![PyPI](https://img.shields.io/github/commits-since/stefantaubert/mean-opinion-score/latest/master.svg)](https://github.com/stefantaubert/mean-opinion-score/compare/v0.0.1...master)
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7669641.svg)](https://doi.org/10.5281/zenodo.7669641)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7670649.svg)](https://doi.org/10.5281/zenodo.7670649)
 
-Python library to evaluate text-to-speech (TTS) mean opinion score (MOS) studies done on Amazon Mechanical Turk (MTurk).
-The calculation of the confidence intervals is done in the same manner as described in (Ribeiro et al., 2011).
+Python library for calculating the mean opinion score (MOS) and 95% confidence interval (CI) of the standard deviation (SD) of text-to-speech (TTS) ratings according to ["Ribeiro, F., Florêncio, D., Zhang, C., & Seltzer, M. (2011). CrowdMOS: An approach for crowdsourcing mean opinion score studies"](https://doi.org/10.1109/ICASSP.2011.5946971). To determine CIs, the authors used a two-way random effects model with the variables: diversity of intrinsic sentence quality, diversity of rater preference, and subjective uncertainty.
 
 ## Installation
 
@@ -22,39 +21,23 @@ pip install mean-opinion-score --user
 ```py
 import numpy as np
 
-from mean_opinion_score import compute_mos, compute_ci95
+from mean_opinion_score import get_ci95, get_mos
 
 _ = np.nan
 
+# columns represent sentences
 ratings = np.array([
-    # columns represent sentences
-    # algorithm 1
-    [
-      [4, 5, _, 4],  # rater 1
-      [4, 4, 4, 5],  # rater 2
-      [_, 3, 5, 4],  # rater 3
-      [_, _, _, _],  # rater 4
-    ],
-    # algorithm 2
-    [
-      [1, 2, _, _],  # rater 1
-      [1, 1, 1, _],  # rater 2
-      [_, 2, 5, 1],  # rater 3
-      [_, 1, _, 1],  # rater 4
-    ]
+    [4, 5, _, 4, _, 3],  # rater 1
+    [4, 4, 4, 5, _, 4],  # rater 2
+    [_, 3, 5, 4, _, 1],  # rater 3
+    [_, _, _, _, _, _],  # rater 4
 ])
 
-alg1_mos = compute_mos(ratings[0])
-alg1_ci95 = compute_ci95(ratings[0])
+mos = get_mos(ratings)
+ci = get_ci95(ratings)
 
-print(f"MOS algorithm 1: {alg1_mos:.2f} ± {alg1_ci95:.4f}")
-# MOS algorithm 1: 4.20 ± 0.6997
-
-alg2_mos = compute_mos(ratings[1])
-alg2_ci95 = compute_ci95(ratings[1])
-
-print(f"MOS algorithm 2: {alg2_mos:.2f} ± {alg2_ci95:.4f}")
-# MOS algorithm 2: 1.60 ± 1.7912
+print(f"MOS: {mos:.2f} ± {ci:.4f}")
+# MOS: 3.85 ± 1.3316
 ```
 
 ## Dependencies
@@ -71,20 +54,22 @@ If you notice an error, please don't hesitate to open an issue.
 ```sh
 # update
 sudo apt update
-# install Python 3.8, 3.9, 3.10 & 3.11 for ensuring that tests can be run
+# install Python 3.6, 3.7, 3.8, 3.9, 3.10 & 3.11 for ensuring that tests can be run
 sudo apt install python3-pip \
+  python3.6 python3.6-dev python3.6-distutils python3.6-venv \
+  python3.7 python3.7-dev python3.7-distutils python3.7-venv \
   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
+python3.11 -m pip install pipenv --user
 
 # check out repo
 git clone https://github.com/stefantaubert/mean-opinion-score.git
 cd mean-opinion-score
 # create virtual environment
-python3.8 -m pipenv install --dev
+python3.11 -m pipenv install --dev
 ```
 
 ## Running the tests
@@ -94,7 +79,7 @@ python3.8 -m pipenv install --dev
 # then, navigate into the directory of the repo (if not already done)
 cd mean-opinion-score
 # activate environment
-python3.8 -m pipenv shell
+python3.11 -m pipenv shell
 # run tests
 tox
 ```
@@ -117,18 +102,18 @@ MIT License
 
 ## Acknowledgments
 
-Calculation and template are based on:
+MOS and CI calculation is taken from:
 
 - 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](https://doi.org/10.1109/ICASSP.2011.5946971)
 
-Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 416228727 – CRC 1410
+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*).
 
 ```txt
-Taubert, S. (2023). mean-opinion-score (Version 0.0.1) [Computer software]. https://doi.org/10.5281/zenodo.7669641
+Taubert, S. (2023). mean-opinion-score (Version 0.0.1) [Computer software]. https://doi.org/10.5281/zenodo.7670649
 ```
 
 ## Changelog

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "mean-opinion-score"
 version = "0.0.1"
-description = "Python library to calculate mean opinion score and standard deviation."
+description = "Library for calculating the mean opinion score and 95% confidence interval of the standard deviation of text-to-speech ratings according to Ribeiro et al. (2011)."
 readme = "README.md"
 requires-python = ">=3.6, <3.12"
 license = {text = "MIT"}

src/mean_opinion_score_tests/helper.py

@@ -1,9 +1,5 @@
 from pathlib import Path
 
-import numpy as np
-
-from mean_opinion_score.calculation import get_ci95, get_mos
-
 
 def get_test_resource_path(name: str) -> Path:
   path = Path(f"src/mean_opinion_score_tests/res/{name}")