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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "bb78ac37-de4f-407a-8fd5-1a269fd937c9",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
]
}
],
"source": [
"# Import necessary libraries and filter warnings\n",
"import warnings\n",
"warnings.filterwarnings(\"ignore\")\n",
"import nbimporter\n",
"import os\n",
"import re\n",
"import numpy as np\n",
"import torchaudio\n",
"from transformers import pipeline\n",
"from text2int import text_to_int\n",
"from isNumber import is_number\n",
"from Text2List import text_to_list\n",
"from convert2list import convert_to_list\n",
"from processDoubles import process_doubles\n",
"from replaceWords import replace_words\n",
"transcriber = pipeline(task=\"automatic-speech-recognition\", model=\"cdactvm/w2v-bert-2.0-hindi_v1\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "02b787e8-6d08-4351-a830-7f7cae7f8243",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7860\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"\n",
"def transcribe(audio):\n",
" # # Process the audio file\n",
" transcript = transcriber(audio)\n",
" text_value = transcript['text']\n",
" print(text_value)\n",
" processd_doubles=process_doubles(text_value)\n",
" converted_to_list=convert_to_list(processd_doubles,text_to_list())\n",
" replaced_words = replace_words(converted_to_list)\n",
" converted_text=text_to_int(replaced_words)\n",
" return converted_text\n",
"\n",
"\n",
"demo = gr.Interface(\n",
" transcribe,\n",
" gr.Audio(sources=\"microphone\", type=\"filepath\"),\n",
" \"text\",\n",
")\n",
"\n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "756c0b55-17b4-4aa0-baac-d8f1c4b003df",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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