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| Metric | Original | Trimmed | Reduction |
|---|---|---|---|
| Vocabulary size | 51,865 tokens | 16,384 tokens | 68.41% |
| Model size | 37,760,640 params | 24,135,936 params | 36.08% |
1from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
2import librosa
3
4# Pipeline function
5processor = AutoProcessor.from_pretrained("alphaedge-ai/whisper-tiny-hin-32768")
6pipe = pipeline(
7 "automatic-speech-recognition",
8 model="alphaedge-ai/whisper-tiny-hin-32768",
9 tokenizer=processor.tokenizer,
10 feature_extractor=processor.feature_extractor,
11 generate_kwargs={"language": "hindi", "task": "transcribe"},
12)
13
14# Loading and resampling at 16 kHz (required by Whisper)
15audio_array, sampling_rate = librosa.load(audio_path, sr=16000)
16
17# Result
18result = pipe(audio_array)
19print("Transcription :", result["text"])@misc{radford2022whisper,
doi = {10.48550/ARXIV.2212.04356},
url = {https://arxiv.org/abs/2212.04356},
author = {Radford, Alec and Kim, Jong Wook and Xu, Tao and Brockman, Greg and McLeavey, Christine and Sutskever, Ilya},
title = {Robust Speech Recognition via Large-Scale Weak Supervision},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}@misc{hf_blogpost_trimming,
title={Introduction to Trimming},
author={Loïck BOURDOIS and Tom AARSEN and Bram VANROY and Christopher AKIKI and Woojun JUNG and Manuel ROMERO and Prithiv SAKTHI},
year={2026},
url={https://huggingface.co/blog/lbourdois/introduction-to-trimming},
}