Duplicate from harish3110/emotion_detection

Co-authored-by: Harish Vadlamani <[email protected]>

.gitattributes

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README.md

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+---
+title: Emotion Detection
+emoji: 🌖
+colorFrom: blue
+colorTo: indigo
+sdk: gradio
+sdk_version: 3.0.19
+app_file: app.py
+pinned: false
+duplicated_from: harish3110/emotion_detection
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from speechbrain.pretrained.interfaces import foreign_class
+import gradio as gr
+
+import warnings
+warnings.filterwarnings("ignore")
+
+# Loading the speechbrain emotion detection model
+learner = foreign_class(
+    source="speechbrain/emotion-recognition-wav2vec2-IEMOCAP",
+    # savedir="/home/harish3110/SeaWord/emotion/nbs/pretrained_models/CustomEncoderWav2vec2Classifier--8353113631630090076",
+    pymodule_file="custom_interface.py", 
+    classname="CustomEncoderWav2vec2Classifier"
+)
+
+# Building prediction function for gradio
+emotion_dict = {
+    'sad': 'Sad', 
+    'hap': 'Happy',
+    'ang': 'Anger',
+    'neu': 'Neutral'
+}
+
+def predict_emotion(audio):
+    out_prob, score, index, text_lab = learner.classify_file(audio.name)
+    return emotion_dict[text_lab[0]]
+
+# Loading gradio interface
+inputs = gr.inputs.Audio(label="Input Audio", type="file")
+outputs = "text"
+title = "Emotion Detection"
+description = "Gradio demo for Emotion Detection. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below."
+gr.Interface(predict_emotion, inputs, outputs, title=title, description=description).launch()

requirements.txt

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+speechbrain
+torchaudio
+transformers