Senselab is a Python package that simplifies building pipelines for speech and voice analysis.
Project description
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.audio import Audio
from senselab.audio.tasks.preprocessing.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.
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