| MiteshPuthran/Speech-Emotion-Analyzer |
1,155 |
|
0 |
0 |
about 3 years ago |
0 |
|
|
mit |
Jupyter Notebook |
| The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python) |
| amanbasu/speech-emotion-recognition |
78 |
|
0 |
0 |
over 5 years ago |
0 |
|
2 |
gpl-3.0 |
Jupyter Notebook |
| Detecting emotions using MFCC features of human speech using Deep Learning |
| loretoparisi/hf-experiments |
37 |
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0 |
0 |
over 3 years ago |
0 |
|
0 |
mit |
Python |
| Experiments with Hugging Face 🔬 🤗 |
| praweshd/speech_emotion_recognition |
23 |
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0 |
0 |
over 2 years ago |
0 |
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0 |
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Jupyter Notebook |
| In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity for their ability to perform well without any input hand-crafted features. Speech emotion on sets obtained from RAVDESS corpus is classified using a conventionally used Support Vector Machine (SVM) and its performance is compared to that of a bidirectional long short-term memory (LSTM). |
| AkishinoShiame/Chinese-Speech-Emotion-Datasets |
23 |
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0 |
0 |
almost 8 years ago |
0 |
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0 |
apache-2.0 |
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| Datasets of A Deep Convolutional Neural Network Based Virtual Elderly Companion Agent. |
| IlyaZaprutski/bluetooth-lamp |
9 |
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0 |
0 |
almost 6 years ago |
0 |
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0 |
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JavaScript |
| Demo project for bluetooth lamp |
| caibolun/AVEC-BDS2018 |
9 |
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0 |
0 |
almost 3 years ago |
0 |
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0 |
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Python |
| Multi-modality Hierarchical Recall based on GBDTs for Bipolar Disorder Classification |
| jpanged/ItsDisturbing |
5 |
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0 |
0 |
almost 9 years ago |
0 |
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0 |
agpl-3.0 |
Python |
| Identifying potential red flags using Watson NLU |
| michen00/unified_multilingual_dataset_of_emotional_human_utterances |
5 |
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0 |
0 |
over 4 years ago |
0 |
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0 |
other |
Jupyter Notebook |
| A unified dataset of multilingual emotional human utterances |
