Welcome to senselab! This is a Python package for streamlining the processing and analysis of behavioral data, such as voice and speech patterns, with robust and reproducible methodologies.

Caution:: this package is still under development and may change rapidly over the next few weeks.

Installation

Install this package via:

pip install senselab

Or get the newest development version via:

pip install git+https://github.com/sensein/senselab.git

Quick start

from senselab.audio.data_structures import Audio
from senselab.audio.tasks.preprocessing import resample_audios

audio1 = Audio.from_filepath('path_to_audio_file.wav')

print("The original audio has a sampling rate of {} Hz.".format(audio1.sampling_rate))
[audio1] = resample_audios([audio1], resample_rate=16000)
print("The resampled audio has a sampling rate of {} Hz.".format(audio1.sampling_rate))

For more detailed information, check out our Getting Started Tutorial.

Why should I use senselab?

• Modular Design: Easily integrate or use standalone transformations for flexible data manipulation.
• Pre-built Pipelines: Access pre-configured pipelines to reduce setup time and effort.
• Reproducibility: Ensure consistent and verifiable results with fixed seeds and version-controlled steps.
• Easy Integration: Seamlessly fit into existing workflows with minimal configuration.
• Extensible: Modify and contribute custom transformations and pipelines to meet specific research needs.
• Comprehensive Documentation: Detailed guides, examples, and documentation for all features and modules.
• Performance Optimized: Efficiently process large datasets with optimized code and algorithms.
• Interactive Examples: Jupyter notebooks provide practical examples for deriving insights from real-world datasets.

Contributing

Please see CONTRIBUTING.md before contributing.

To find out what's currently in progress, please check the Project Board.