Automatic Speech Recognition
Transformers
PyTorch
Safetensors
English
speecht5
audio
speech
speech2text
ASR
asr
ASR-punctuation-sensitive
encoder-decoder-for-asr
Instructions to use seba3y/speecht5-asr-punctuation-sensitive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seba3y/speecht5-asr-punctuation-sensitive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seba3y/speecht5-asr-punctuation-sensitive")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seba3y/speecht5-asr-punctuation-sensitive") model = AutoModelForSpeechSeq2Seq.from_pretrained("seba3y/speecht5-asr-punctuation-sensitive") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": false, | |
| "feature_extractor_type": "SpeechT5FeatureExtractor", | |
| "feature_size": 1, | |
| "fmax": 7600, | |
| "fmin": 80, | |
| "frame_signal_scale": 1.0, | |
| "hop_length": 16, | |
| "mel_floor": 1e-10, | |
| "num_mel_bins": 80, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "SpeechT5Processor", | |
| "reduction_factor": 2, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "win_function": "hann_window", | |
| "win_length": 64 | |
| } | |