speech-emotion-recognition | Speaker independent emotion recognition | Speech library

by harry-7 Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | speech-emotion-recognition Summary

speech-emotion-recognition is a Python library typically used in Artificial Intelligence, Speech, Deep Learning, Keras, Neural Network applications. speech-emotion-recognition has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Speaker independent emotion recognition

Support

Quality

Security

License

Reuse

Support

speech-emotion-recognition has a low active ecosystem.

It has 174 star(s) with 77 fork(s). There are 14 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 20 have been closed. On average issues are closed in 26 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 0 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 is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

speech-emotion-recognition releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

speech-emotion-recognition saves you 1574 person hours of effort in developing the same functionality from scratch.

It has 3498 lines of code, 34 functions and 35 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

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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

One hot encoded output to categorical value from a ML model

Python beginner ML project issues

QUESTION

One hot encoded output to categorical value from a ML model

Asked 2021-Jul-19 at 13:51

In my one .py file I created a model and saved the .pkl file of it to use afterward for analysis. The model is formed using the code from this kaggle emotional data set https://www.kaggle.com/shivamburnwal/speech-emotion-recognition The issue is that when I am using this code's model to detect the emotion of new audio then the output is in one hot encoded format. Is there any way using which I can get the actual emotion('happy','fear' etc.) instead of 1's and 0's.

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ANSWER

Answered 2021-Jul-19 at 13:51

prediction output is a list like this:

Source https://stackoverflow.com/questions/68431274

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).

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ANSWER

Answered 2020-Aug-18 at 18:39

Use model.predict() on your new audio file. That should return your desired output.

Source https://stackoverflow.com/questions/63474640

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.

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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