speech-emotion-recognition | speech emotion recognition | Speech library
kandi X-RAY | speech-emotion-recognition Summary
kandi X-RAY | speech-emotion-recognition Summary
speech-emotion-recognition is a Python library typically used in Artificial Intelligence, Speech, Deep Learning, Tensorflow, Neural Network applications. speech-emotion-recognition has no bugs, it has no vulnerabilities and it has low support. However speech-emotion-recognition build file is not available. You can download it from GitHub.
speech emotion recognition using a convolutional recurrent networks based on IEMOCAP
speech emotion recognition using a convolutional recurrent networks based on IEMOCAP
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Quality
Security
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Support
speech-emotion-recognition has a low active ecosystem.
It has 279 star(s) with 120 fork(s). There are 11 watchers for this library.
It had no major release in the last 6 months.
There are 7 open issues and 34 have been closed. On average issues are closed in 15 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of speech-emotion-recognition is current.
Quality
speech-emotion-recognition has 0 bugs and 139 code smells.
Security
speech-emotion-recognition has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
speech-emotion-recognition code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
speech-emotion-recognition does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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speech-emotion-recognition releases are not available. You will need to build from source code and install.
speech-emotion-recognition has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
speech-emotion-recognition saves you 609 person hours of effort in developing the same functionality from scratch.
It has 1419 lines of code, 53 functions and 10 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed speech-emotion-recognition and discovered the below as its top functions. This is intended to give you an instant insight into speech-emotion-recognition implemented functionality, and help decide if they suit your requirements.
- Builds the convolutional network
- Leaky relu
- Max pool op
- Linear regression
- 2d convolution layer
- Wrapper for batch normalization
- Attention function
- Batch norm
- Train the model
- A leaky_relu
- Loads data from pickle file
- Convert dense labels to one - hot matrix
- Batch normalization
- Attention layer
- Cacrnn layer
- Reads the IEMOCAP dataset
- Generate a label for the given emotion
- Read a wave file
Get all kandi verified functions for this library.
speech-emotion-recognition Key Features
No Key Features are available at this moment for speech-emotion-recognition.
speech-emotion-recognition Examples and Code Snippets
No Code Snippets are available at this moment for speech-emotion-recognition.
Community Discussions
Trending Discussions on speech-emotion-recognition
QUESTION
Python beginner ML project issues
Asked 2020-Dec-18 at 19:42
So I copied some code to try and figure out machine learning in python(link = https://data-flair.training/blogs/python-mini-project-speech-emotion-recognition). Overall it worked out great but now I do not know how to use it (input a file of my own and analyze it).
...ANSWER
Answered 2020-Aug-18 at 18:39Use model.predict() on your new audio file. That should return your desired output.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install speech-emotion-recognition
You can download it from GitHub.
You can use speech-emotion-recognition like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use speech-emotion-recognition like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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