# entrainment-metrics
[](https://entrainment-metrics.readthedocs.io/en/latest/?badge=latest)
entrainment-metrics is all about being able to measure entrainment. Entrainment in spoken dialogue is commonly defined as a tendency of a speaker to adapt some properties of her speech to match her interlocutor’s. With this library you’ll be able to measure entrainment along one dimension: acoustic-prosodic (a/p) features.
Checkout [the docs](https://entrainment-metrics.readthedocs.io/en/latest/) and the [Getting started](https://entrainment-metrics.readthedocs.io/en/latest/usage/getting_started.html#getting-started) page for a deeper dive into the library!
## Installation
- To use entrainment_metrics, first install it using pip:
```bash
pip install entrainment_metrics
```
- Speech feature extraction
If you'll be using praat for feature extraction it's also required the command-line tool ffmpeg to be installed on your system, which is available from most package managers:
```bash
# on Ubuntu or Debian
sudo apt update && sudo apt install ffmpeg
# on Arch Linux
sudo pacman -S ffmpeg
# on MacOS using Homebrew (https://brew.sh/)
brew install ffmpeg
# on Windows using Chocolatey (https://chocolatey.org/)
choco install ffmpeg
# on Windows using Scoop (https://scoop.sh/)
scoop install ffmpeg
```
And for installing praat on Ubuntu or Debian:
```bash
sudo apt update && sudo apt install praat
```
Raw data
{
"_id": null,
"home_page": "https://github.com/erikernst4/entrainment-metrics",
"name": "entrainment-metrics",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8,<3.11",
"maintainer_email": "",
"keywords": "speech,prosody,speech-analysis,entrainment,prosodic-analysis",
"author": "E. Ernst, A. Gravano, R. G\u00e1lvez",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/03/6a/a38cbe8c83d4324f2f35235fe4d34d145c2cf35e5bf6a22f519cae42069e/entrainment_metrics-1.0.5.tar.gz",
"platform": null,
"description": "# entrainment-metrics\n[](https://entrainment-metrics.readthedocs.io/en/latest/?badge=latest)\n\nentrainment-metrics is all about being able to measure entrainment. Entrainment in spoken dialogue is commonly defined as a tendency of a speaker to adapt some properties of her speech to match her interlocutor\u2019s. With this library you\u2019ll be able to measure entrainment along one dimension: acoustic-prosodic (a/p) features.\n\nCheckout [the docs](https://entrainment-metrics.readthedocs.io/en/latest/) and the [Getting started](https://entrainment-metrics.readthedocs.io/en/latest/usage/getting_started.html#getting-started) page for a deeper dive into the library!\n\n## Installation\n- To use entrainment_metrics, first install it using pip:\n\n```bash\npip install entrainment_metrics\n```\n- Speech feature extraction\nIf you'll be using praat for feature extraction it's also required the command-line tool ffmpeg to be installed on your system, which is available from most package managers:\n\n```bash\n# on Ubuntu or Debian\nsudo apt update && sudo apt install ffmpeg\n\n# on Arch Linux\nsudo pacman -S ffmpeg\n\n# on MacOS using Homebrew (https://brew.sh/)\nbrew install ffmpeg\n\n# on Windows using Chocolatey (https://chocolatey.org/)\nchoco install ffmpeg\n\n# on Windows using Scoop (https://scoop.sh/)\nscoop install ffmpeg\n```\nAnd for installing praat on Ubuntu or Debian:\n\n```bash\nsudo apt update && sudo apt install praat\n```\n",
"bugtrack_url": null,
"license": "Apache-2.0",
"summary": "Measure acoustic-prosodic entrainment in speech",
"version": "1.0.5",
"project_urls": {
"Documentation": "https://entrainment-metrics.readthedocs.io/en/latest/",
"Homepage": "https://github.com/erikernst4/entrainment-metrics",
"Repository": "https://github.com/erikernst4/entrainment-metrics"
},
"split_keywords": [
"speech",
"prosody",
"speech-analysis",
"entrainment",
"prosodic-analysis"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "33a7a6a4c42b237537fe67a3824ead5d04f905ed2436b818a1f729a6474f748d",
"md5": "01fe7cc14acab213e4d18e50218a256a",
"sha256": "c5348b94e17f29d58bd4bf840678480b1b69b4e42d44e7854bb7f9f4f06eaf56"
},
"downloads": -1,
"filename": "entrainment_metrics-1.0.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "01fe7cc14acab213e4d18e50218a256a",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8,<3.11",
"size": 18826,
"upload_time": "2023-12-18T00:50:54",
"upload_time_iso_8601": "2023-12-18T00:50:54.051506Z",
"url": "https://files.pythonhosted.org/packages/33/a7/a6a4c42b237537fe67a3824ead5d04f905ed2436b818a1f729a6474f748d/entrainment_metrics-1.0.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "036aa38cbe8c83d4324f2f35235fe4d34d145c2cf35e5bf6a22f519cae42069e",
"md5": "4902bc6fdd1cd71d10de28ad260c6e8c",
"sha256": "6e054980a07170f1713cfd2a7c8beb547a5ceebbc1ad55c297730aa8bf3516d9"
},
"downloads": -1,
"filename": "entrainment_metrics-1.0.5.tar.gz",
"has_sig": false,
"md5_digest": "4902bc6fdd1cd71d10de28ad260c6e8c",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8,<3.11",
"size": 14417,
"upload_time": "2023-12-18T00:50:55",
"upload_time_iso_8601": "2023-12-18T00:50:55.439607Z",
"url": "https://files.pythonhosted.org/packages/03/6a/a38cbe8c83d4324f2f35235fe4d34d145c2cf35e5bf6a22f519cae42069e/entrainment_metrics-1.0.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-12-18 00:50:55",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "erikernst4",
"github_project": "entrainment-metrics",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"requirements": [],
"lcname": "entrainment-metrics"
}
JSON
