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ZeeshanGeoPk
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ZeeshanGeoPk
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This repository contains a fine-tuned Whisper ASR (Automatic Speech Recognition) model for the Haitian language. The model is hosted on Hugging Face and is ready for use.
The model achieved a Word Error Rate (WER) of 0.19126, indicating high accuracy in transcribing spoken Haitian to written text.
The model was trained with a learning rate of 1e-5.
You can use this model directly from the Hugging Face Model Hub. Here's a simple example in Python:
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from transformers import WhisperProcessor, WhisperForConditionalGenerationimport torchaudio# load model and processorprocessor = WhisperProcessor.from_pretrained("ZeeshanGeoPk/haitian-speech-to-text")model = WhisperForConditionalGeneration.from_pretrained("ZeeshanGeoPk/haitian-speech-to-text")# read audio filessample_path = "path/to/audio.wav"# load audio file using torchaudiowaveform, sample_rate = torchaudio.load(sample_path)# resample if needed (Whisper model requires 16kHz)if sample_rate != 16000: resampler = torchaudio.transforms.Resample(sample_rate, 16000) waveform = resampler(waveform) sample_rate = 16000# ensure mono channelif waveform.shape[0] > 1: waveform = waveform.mean(dim=0, keepdim=True)# process audio using Whisper processorinput_features = processor(waveform.numpy(), sampling_rate=sample_rate, return_tensors="pt").input_features# generate token idspredicted_ids = model.generate(input_features)# decode token ids to texttranscription = processor.batch_decode(predicted_ids, skip_special_tokens=True)print(transcription)