# High Accuracy Audio Classification

A Turkish gender classification model fine-tuned from facebook/wav2vec2-base, trained on the common_voice_17_0 dataset with a test set accuracy of 84.79%

An emotion classification model fine-tuned based on shhossain/whisper-tiny-bn, capable of recognizing 7 basic emotions in Bengali

This model is a fine-tuned version of wav2vec2-base-ft-keyword-spotting on the superb dataset for audio classification tasks, optimized through quantization and structured pruning.

An audio classification model based on the TRillsson3 architecture, fine-tuned on the superb dataset for keyword recognition tasks

A fine-tuned Urdu audio emotion classification model based on facebook/wav2vec2-large-xlsr-53, supporting recognition of four emotions: anger, happiness, calmness, and sadness.