https://github.com/alan-turing-institute/netts

Toolbox for creating networks capturing semantic content of speech transcripts.

https://github.com/alan-turing-institute/netts

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    3 of 7 committers (42.9%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (15.4%) to scientific vocabulary

Keywords

graph-theory hut23 networks nlp python semantic-content transcripts

Keywords from Contributors

hut23-rcp
Last synced: 6 months ago · JSON representation

Repository

Toolbox for creating networks capturing semantic content of speech transcripts.

Basic Info
Statistics
  • Stars: 8
  • Watchers: 1
  • Forks: 1
  • Open Issues: 43
  • Releases: 9
Archived
Topics
graph-theory hut23 networks nlp python semantic-content transcripts
Created over 4 years ago · Last pushed almost 3 years ago
Metadata Files
Readme License

README.md

netts - NETworks of Transcript Semantics

GitHub release PyPI pyversions codecov Code style: black Imports: isort

Toolbox for constructing semantic speech networks from speech transcripts.

About

The algorithms in this toolbox create a semantic speech graph from transcribed speech. Speech transcripts are short paragraphs of largely raw, uncleaned speech-like text. For example:

'I see a man and he is wearing a jacket. He is standing in the dark against a light post. On the picture there seems to be like a park and... Or trees but in those trees there are little balls of light reflections as well. I cannot see the... Anything else because it’s very dark. But the man on the picture seems to wear a hat and he seems to have a hoodie on as well. The picture is very mysterious, which I like about it, but for me I would like to understand more about the picture.' -- Example Transcript

Below is the semantic speech graph constructed from this text.

Semantic speech graph example Figure 1. Semantic Speech Graph. Nodes represents an entity mentioned by the speaker (e.g. I, man, jacket). Edges represent relations between nodes mentioned by the speaker (e.g. see, has on).

Getting started

Read the full documentation here.

Where to get it

You can install the latest release from PyPi

bash pip install netts

or get the latest development version from GitHub (not stable)

bash pip install git+https://github.com/alan-turing-institute/netts

Additional dependencies

Netts requires the Java Runtime Environment. Instructions for downloading and installing for your operating system can be found here.

Netts also requires a few additional dependencies to work which you can download with the netts CLI that was installed by pip

bash netts install

Basic usage

The quickest way to process a transcript is with the CLI.

bash netts run transcript.txt outputs

where transcript.txt is a text file containing transcribed speech and outputs is the name of a directory to write the outputs to. Additional logging information can be found in netts_log.log.

Contributors

Netts was written by Caroline Nettekoven in collaboration with Sarah Morgan.

Netts was packaged in collaboration with Oscar Giles, Iain Stenson and Helen Duncan.

Owner

  • Name: The Alan Turing Institute
  • Login: alan-turing-institute
  • Kind: organization
  • Email: info@turing.ac.uk

The UK's national institute for data science and artificial intelligence.

GitHub Events

Total
  • Issues event: 2
  • Issue comment event: 1
Last Year
  • Issues event: 2
  • Issue comment event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 418
  • Total Committers: 7
  • Avg Commits per committer: 59.714
  • Development Distribution Score (DDS): 0.51
Past Year
  • Commits: 34
  • Committers: 2
  • Avg Commits per committer: 17.0
  • Development Distribution Score (DDS): 0.324
Top Committers
Name Email Commits
Oscar Giles o****s@t****k 205
Iain-S 2****S 67
CN 3****m 43
CN c****n@g****m 42
Helen Duncan h****n@t****k 35
rkdan r****3@c****k 23
pre-commit p****t@e****m 3
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 36
  • Total pull requests: 65
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 11 days
  • Total issue authors: 5
  • Total pull request authors: 5
  • Average comments per issue: 1.33
  • Average comments per pull request: 0.45
  • Merged pull requests: 43
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: 15 days
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • OscartGiles (25)
  • Iain-S (8)
  • weiwei-wch (1)
  • helendduncan (1)
  • mhauru (1)
Pull Request Authors
  • Iain-S (45)
  • OscartGiles (14)
  • rkdan (3)
  • carobellum (2)
  • helendduncan (1)
Top Labels
Issue Labels
Type: documentation (4) Type: enhancement (2) good first issue (1) Type: Learning/Exploritory (1) Type: bug (1)
Pull Request Labels
do-not-merge (7) WIP (2)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 27 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 7
  • Total maintainers: 4
pypi.org: netts

Toolbox for constructing NETworks of Transcript Semantics.

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 27 Last month
Rankings
Dependent packages count: 10.1%
Stargazers count: 18.5%
Average: 20.8%
Dependent repos count: 21.6%
Forks count: 22.6%
Downloads: 31.4%
Last synced: 6 months ago

Dependencies

pyproject.toml pypi
  • black ^22.3.0 develop
  • devtools ^0.8.0 develop
  • flake8 ^3.9.2 develop
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  • pre-commit ^2.14.0 develop
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  • safety ^1.10.3 develop
  • matplotlib ^3.4.3
  • networkx ^2.6.2
  • nltk ^3.6.2
  • numpy ^1.22.2
  • pandas ^1.3.2
  • pydantic ^1.8.2
  • pyopenie ^0.2.0
  • python >=3.8,<3.11
  • requests ^2.26.0
  • rtoml ^0.7.0
  • stanza ^1.2.3
  • tqdm ^4.62.2
  • typer ^0.4.1
poetry.lock pypi
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  • joblib 1.1.0
  • kiwisolver 1.4.0
  • matplotlib 3.5.1
  • networkx 2.7.1
  • nltk 3.7
  • numpy 1.22.3
  • packaging 21.3
  • pandas 1.4.1
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  • protobuf 3.19.4
  • pydantic 1.9.0
  • pyopenie 0.2.0
  • pyparsing 3.0.7
  • python-dateutil 2.8.2
  • python-dotenv 0.19.2
  • pytz 2021.3
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  • requests 2.27.1
  • rtoml 0.7.1
  • setuptools-scm 6.4.2
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  • torch 1.11.0
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