List of potential libraries and API services to add

PsychoinformaticsLab / pliers

Automated feature extraction in Python

https://pliers.readthedocs.io/en/latest/

BSD 3-Clause "New" or "Revised" License

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List of potential libraries and API services to add #34

Open tyarkoni opened 8 years ago

tyarkoni commented 8 years ago

This is a standing issue for tracking potential libraries and API services to wrap in pliers.

Multimodal/major APIs

[ ] Amazon Rekognition
[x] Microsoft Azure APIs

Audio

[x] Librosa
[ ] A-weighting of AudioStims
[ ] madmom

Image

[x] face_recognition (this one should be trivial)
[ ] neural-doodle and neural-enhance
[ ] OpenPose (with Python API)

Language

[x] spaCy
[ ] DeepSpeech

qmac commented 7 years ago

https://github.com/abhishekbanthia/Public-APIs

adelavega commented 7 years ago

Amazon Rekognition - https://aws.amazon.com/rekognition/

tyarkoni commented 6 years ago

@qmac--I think we should make Amazon Rekognition our highest priority for addition. The video features look amazing.

PeerHerholz commented 6 years ago

Ahoi hoi folks,

here are some more ideas/suggestions. Spoiler: all auditory!

[ ] remaining librosa features (beat/tempo)
[ ] bregman toolkit (might need python 2 -> 3 conversion)
[ ] essentia -> cool stuff like mood detection, segmentation and classification, integration with AcousticBrainz
[ ] pyaudioanalysis -> feature extraction, segmentation, classification, pre-trained models included, speaker diarization, emotion recognition, etc.
[x] AudioSet -> (pre-trained) CNNs and huge data set
[ ] aubio -> feature extraction

rbroc commented 4 years ago

Pointer to new potentially interesting library tokenizers, although some tokenization options area will already be covered by the transformers wrapper.

rbroc commented 4 years ago

Library for co-reference resolution which works as pipeline extension for SpaCy: neuralcoref.

Finds expressions in text that refer to same entity and groups them in clusters.

At token level, can yield info of which reference cluster(s) (if any) the token expression is part of. At document level, can be used to extract metrics such as number of entities named, and number of mentions per entity.

Potential use case: tracking mentions of characters along a narrative/dialogue.

rbroc commented 4 years ago

New pretty cool object recognition model trained with contrastive learning: https://github.com/google-research/simclr. Paper: https://arxiv.org/abs/2002.05709

rbroc commented 4 years ago

Auditory English Lexicon Project (auditory lexical norms): haven't taken a close look yet, but for future reference, paper here: https://doi.org/10.3758/s13428-020-01352-0, website with data here: https://inetapps.nus.edu.sg/aelp/