Speech-Emotion-Recognition | Speech emotion recognition implemented in Keras ( LSTM | Machine Learning library

by Renovamen 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, Machine Learning, Deep Learning, Pytorch, 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.

用 LSTM、CNN、SVM、MLP 进行语音情感识别，Keras 实现。. 改进了特征提取方式，识别准确率提高到了 80% 左右。原来的版本的存档在 First-Version 分支。. English Document | 中文文档.

Support

Quality

Security

License

Reuse

Support

Speech-Emotion-Recognition has a low active ecosystem.

It has 615 star(s) with 169 fork(s). There are 14 watchers for this library.

It had no major release in the last 6 months.

There are 16 open issues and 23 have been closed. On average issues are closed in 88 days. There are 3 open pull requests and 0 closed 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.

Installation instructions are not available. Examples and code snippets are available.

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.

Extract data from opensmile
Load feature
Get the path to the data directory
Opens a single feature file
Compute the min and max of a list of files
Extract features from librosa file
Calculate the centroids of features
Create a trained model
Create an MLPClassifier
Create a new SVC model
Predict probabilities for the given samples
Predict for the given samples
Parse command line options
Load configuration from file
Train the model
Plot the curve
Predict class

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

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.

...

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).

...

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 .

Find more information at: