Metadata-Version: 2.1
Name: ERL-Spanish
Version: 1.0.4
Summary: ERL: Emotion Recognition Library
Home-page: https://github.com/estefaaa02/ERL
Author: Mario Gómez, Estefanía Pérez, Victoria Núñez
Author-email: mgomezcam@unbosque.edu.co, eperezt@unbosque.edu.co, vnunezd@unbosque.edu.co
License: GPLv3 License
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: pyaudioanalysis (==0.3.7)
Requires-Dist: pydub
Requires-Dist: audiosegment (==0.23.0)
Requires-Dist: eyed3 (==0.9.6)
Requires-Dist: speechrecognition (==3.8.1)
Requires-Dist: google-cloud-speech (>=2.9.0)
Requires-Dist: nltk (==3.2.5)
Requires-Dist: pandas (==1.3.4)
Requires-Dist: numpy (==1.19.2)
Requires-Dist: keras (==2.6.0)
Requires-Dist: sklearn
Requires-Dist: matplotlib (==3.4.3)
Requires-Dist: tensorflow (==2.6.0)
Requires-Dist: tqdm

# ERL: Emotion Recognition Library
ERL is a Python library that does emotion recognition through audio. With this library you can recognize emotions using audio signals, the text extracted from the audio or using both.

## Installation
 - Clone the source of this library: `https://github.com/estefaaa02/ERL.git`
 - Install library: `pip install -e .`
### Note:
- If using Windows download the PyAudio wheel for Windows and install it using `pip install`.
- If using Linux install the PyAudio library using `pip install pyaudio`
- If using Linux run `apt install libasound2-dev portaudio19-dev libportaudio2 libportaudiocpp0 ffmpeg`
- By doing `pip install -e . `you are installing the necessary dependencies for the library to work
## Emotion classification example

    from ERL import PredictionsModule
    
    print("PredicciÃ³n Audio: ", PredictionsModule.predict_emotion_audio_svm('ERL/data/es/f_ans002aes.wav'))
    print("PredicciÃ³n Texto: ", PredictionsModule.predict_emotion_text_cnn('ERL/data/es/f_ans002aes.wav'))
    print("PredicciÃ³n Bimodal: ", PredictionsModule.predict_emotion_bimodal('ERL/data/es/f_ans002aes.wav'))


