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import torch |
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from transformers import Wav2Vec2ForCTC, Wav2Vec2Tokenizer |
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from urllib.request import urlopen |
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from io import BytesIO |
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import soundfile as sf |
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import numpy as np |
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model_name = "arham061/speecht5_finetuned_voxpopuli_nl" |
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model = Wav2Vec2ForCTC.from_pretrained(model_name) |
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tokenizer = Wav2Vec2Tokenizer.from_pretrained(model_name) |
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buck2uni = { |
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u"\u0627": "A", |
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u"\u0675": "A", |
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u"\u0673": "A", |
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u"\u0630": "A", |
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u"\u0622": "AA", |
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u"\u0628": "B", |
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u"\u067E": "P", |
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u"\u062A": "T", |
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u"\u0637": "T", |
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u"\u0679": "T", |
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u"\u062C": "J", |
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u"\u0633": "S", |
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u"\u062B": "S", |
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u"\u0635": "S", |
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u"\u0686": "CH", |
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u"\u062D": "H", |
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u"\u0647": "H", |
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u"\u0629": "H", |
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u"\u06DF": "H", |
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u"\u062E": "KH", |
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u"\u062F": "D", |
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u"\u0688": "D", |
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u"\u0630": "Z", |
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u"\u0632": "Z", |
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u"\u0636": "Z", |
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u"\u0638": "Z", |
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u"\u068E": "Z", |
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u"\u0631": "R", |
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u"\u0691": "R", |
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u"\u0634": "SH", |
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u"\u063A": "GH", |
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u"\u0641": "F", |
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u"\u06A9": "K", |
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u"\u0642": "K", |
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u"\u06AF": "G", |
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u"\u0644": "L", |
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u"\u0645": "M", |
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u"\u0646": "N", |
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u"\u06BA": "N", |
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u"\u0648": "O", |
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u"\u0649": "Y", |
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u"\u0626": "Y", |
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u"\u06CC": "Y", |
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u"\u06D2": "E", |
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u"\u06C1": "H", |
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u"\u064A": "E", |
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u"\u06C2": "AH", |
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u"\u06BE": "H", |
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u"\u0639": "A", |
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u"\u0643": "K", |
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u"\u0621": "A", |
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u"\u0624": "O", |
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u"\u060C": "", |
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} |
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def transString(string, reverse=0): |
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"""Given a Unicode string, transliterate into Buckwalter. To go from |
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Buckwalter back to Unicode, set reverse=1""" |
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for k, v in buck2uni.items(): |
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if not reverse: |
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string = string.replace(k, v) |
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else: |
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string = string.replace(v, k) |
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return string |
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def generate_audio(text): |
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roman_urdu = transString(text) |
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inputs = tokenizer(roman_urdu, return_tensors="pt").input_values |
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with torch.no_grad(): |
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logits = model(inputs).logits |
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predicted_ids = torch.argmax(logits, dim=-1) |
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audio = tokenizer.decode(predicted_ids[0], skip_special_tokens=True) |
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return audio |
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def main(): |
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input_text_urdu = input("Enter text in Urdu: ") |
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audio_output = generate_audio(input_text_urdu) |
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sf.write("output.wav", audio_output, samplerate=22050) |
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print("Audio generated and saved as 'output.wav'") |
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if __name__ == "__main__": |
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main() |