Generate realistic, synthetic call center conversations
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Updated
Dec 2, 2023 - Jupyter Notebook
Generate realistic, synthetic call center conversations
Audio Embeddings using VGGish
Audio Deep Learning Project in Java
Re-Implementation of Google Research's VGGish model used for extracting audio features using Pytorch with GPU support.
Visualizations of music semantics calculus using Spotify and deep embeddings.
Generate audio embedding out of pruned L3
Directly from voice, recognise speaker emotion, intensity, & sentiment in speaker utterances.
Audio encoding authentication and validation library for verifying audio as being from a trusted source
SERVER: Multi-modal Speech Emotion Recognition using Transformer-based and Vision-based Embeddings
Extract audio embeddings from an audio file using Python
Audio search using Azure Cognitive Search
Pytorch port of Google Research's VGGish model used for extracting audio features.
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