| It is a broad category with many specific applications, some of which include: | |
| acoustic scene classification: label audio with a scene label ("office", "beach", "stadium") | |
| acoustic event detection: label audio with a sound event label ("car horn", "whale calling", "glass breaking") | |
| tagging: label audio containing multiple sounds (birdsongs, speaker identification in a meeting) | |
| music classification: label music with a genre label ("metal", "hip-hop", "country") | |
| from transformers import pipeline | |
| classifier = pipeline(task="audio-classification", model="superb/hubert-base-superb-er") | |
| preds = classifier("https://huggingface.co/datasets/Narsil/asr_dummy/resolve/main/mlk.flac") | |
| preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds] | |
| preds | |
| [{'score': 0.4532, 'label': 'hap'}, | |
| {'score': 0.3622, 'label': 'sad'}, | |
| {'score': 0.0943, 'label': 'neu'}, | |
| {'score': 0.0903, 'label': 'ang'}] | |
| Automatic speech recognition | |
| Automatic speech recognition (ASR) transcribes speech into text. |