These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
vit-explain
pyAudioAnalysis is a Python library covering a wide range of audio analysis tasks. Through pyAudioAnalysis you can:
- Extract audio features and representations (e.g. mfccs, spectrogram, chromagram)
- Train, parameter tune and evaluate classifiers of audio segments
- Classify unknown sounds
- Detect audio events and exclude silence periods from long recordings
- Perform supervised segmentation (joint segmentation - classification)
- Perform unsupervised segmentation (e.g. speaker diarization) and extract audio thumbnails
- Train and use audio regression models (example application: emotion recognition)
- Apply dimensionality reduction to visualize audio data and content similarities
About the tool
You can click on the links to see the associated tools
Tool type(s):
Objective(s):
Purpose(s):
Country of origin:
Lifecycle stage(s):
Type of approach:
Maturity:
Usage rights:
License:
Target users:
Programming languages:
Github stars:
- 636
Github forks:
- 75
Use Cases
There is no use cases for this tool yet.
Would you like to submit a use case for this tool?
If you have used this tool, we would love to know more about your experience.
Add use case