Audio Classification
Keras
speech_emotion_recognition
Mel-Frequency Cepstral Coefficients
wav2vec2
bi-lstm
cnn
Instructions to use Sharath45/SPEECH_EMOTION_RECOGNITION with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Sharath45/SPEECH_EMOTION_RECOGNITION with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Sharath45/SPEECH_EMOTION_RECOGNITION") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4e98486c361e2d24ab77613f4a6528a569d02f450fe6e1d222a84084c7c5e2b
- Size of remote file:
- 564 MB
- SHA256:
- abcd5779b6c12d19356ee92129b659e868918c3cc607366f21e01a61007b0497
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