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https://github.com/dhchenx/speech-feature-kit
A python wrapper for speech feature extractoin
https://github.com/dhchenx/speech-feature-kit
emotion-analysis mfcc-features speech-emotion-recognition speech-feature volume-analysis
Last synced: about 1 month ago
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A python wrapper for speech feature extractoin
- Host: GitHub
- URL: https://github.com/dhchenx/speech-feature-kit
- Owner: dhchenx
- License: mit
- Created: 2021-10-14T12:51:57.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-12-05T18:01:07.000Z (about 3 years ago)
- Last Synced: 2024-09-20T09:12:47.047Z (4 months ago)
- Topics: emotion-analysis, mfcc-features, speech-emotion-recognition, speech-feature, volume-analysis
- Language: Python
- Homepage:
- Size: 12.3 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# Speech Feature Kit
A Python wrapper for convenient speech feature extraction
## Installation
```python
pip install speech-features-kit
```
## Functions
1. MFCC feature analysis
2. Volume analysis
3. Emotion analysis
## Example of emotion analysis
```python
from speech_features_kit.Emotion.speech_toolkit import SpeechEmotionToolkit
# set the path of pre-trained model for speech emotion model
# the used model here is optimized for Chinese speech; however, it is possible you can train your own model.
speech_kit = SpeechEmotionToolkit()
# load the model
speech_kit.load()
# obtain emotion list with timestamp given an audio file
list_emo, list_timestamp = speech_kit.get_emotion_list_by_blocks(audio_file="../data/english.wav",
num_sec_each_file=1)
# print the list of emotion over timestamp
print("Time interval\tEmotion")
for idx, e in enumerate(list_emo):
print(list_timestamp[idx], "\t", e)
```
## Note
Other functions please see the examples folder!