fine-tune the pre-trained OpenAI Whisper model for audio classification in PyTorch.
Audio classification is an important task that can be applied in various scenarios, such as speech dialogue detection, sentiment analysis, music genre recognition, environmental sound identification, etc.
OpenAI Whisper is an excellent model for audio classification that achieved state-of-the-art results on several benchmarks. It is based on the transformer architecture and uses self-attention to process audio inputs. OpenAI Whisper can recognize speech and audio from different languages, accents, and domains with high accuracy and robustness.
classify various sounds by fine-tuning the OpenAI Whisper model from Hugging Face in the PyTorch deep learning library. load the pre-trained model, prepare a custom audio dataset, train the model on the dataset, and evaluate the model performance.