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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "source": [
+ "#Latviešu valodas runas atpazīšana\n",
+ "\n",
+ "Šajā bloknotā ir rīki latviešu valodas runas atpazīšanai. Tiek izmantots LU MII AiLab izveidotais [runas atpazīšanas modelis](https://huggingface.co/AiLab-IMCS-UL/whisper-large-v3-lv-late-cv17), kas veidots izmantojot [Balsu talkā](https://balsutalka.lv/) savāktos datus.\n",
+ "\n",
+ "Lai veiktu runas atpazīšanu audio failā sekojiet zemāk uzskaitītajiem soļiem."
+ ],
+ "metadata": {
+ "id": "zZBBTnW-aThp"
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "##1. Nomainiet izpildlaika veidu uz T4 GPU\n",
+ "\n",
+ "Lai to izdarītu galvenajā izvēlnē šīs lapas augšpusē ejiet uz `Izpildlaiks` -> `Mainīt izpildlaika veidu` un izvēlieties `T4 GPU`\n",
+ "\n",
+ ""
+ ],
+ "metadata": {
+ "id": "GALJps6fDlQD"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "#@title 2. Nospiediet uz atskaņošanas pogas, lai ielādētu nepieciešamos rīkus.\n",
+ "\n",
+ "import ipywidgets as widgets\n",
+ "from IPython.display import clear_output\n",
+ "import torch\n",
+ "from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline\n",
+ "\n",
+ "uploader = widgets.FileUpload(description='Izvēlieties audio', accept='audio/*', multiple=False)\n",
+ "# uploader = widgets.FileUpload(multiple=False)\n",
+ "display(uploader)"
+ ],
+ "metadata": {
+ "id": "zLDYIFciCMTw",
+ "cellView": "form"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "##3. Izvēlieties audio failu\n",
+ "Pēc rīku ielādes parādīsies poga \"Izvēlieties audio\", nospiediet to un izvēlieties audio failu kurā atpazīt latviešu valodas runu."
+ ],
+ "metadata": {
+ "id": "QxsuN4r0QGnl"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# @title 4. Palaidiet runas atpazīšanas procesu\n",
+ "\n",
+ "if len(uploader.data) == 0:\n",
+ " display(widgets.HTML(\n",
+ " value=\"Audio fails nav izvēlēts, lūdzu izvēlieties audio failu!
\"\n",
+ " ))\n",
+ "else:\n",
+ "\n",
+ " display(widgets.HTML(\n",
+ " value=\"Notiek ielāde...
\"\n",
+ " ))\n",
+ "\n",
+ " device = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n",
+ " torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32\n",
+ "\n",
+ " model_id = \"AiLab-IMCS-UL/whisper-large-v3-lv-late-cv17\"\n",
+ "\n",
+ " model = AutoModelForSpeechSeq2Seq.from_pretrained(\n",
+ " model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=False, use_safetensors=True\n",
+ " ).to(device)\n",
+ "\n",
+ " processor = AutoProcessor.from_pretrained(model_id)\n",
+ "\n",
+ " pipe = pipeline(\n",
+ " \"automatic-speech-recognition\",\n",
+ " generate_kwargs={\"language\": \"latvian\", \"task\": \"transcribe\"},\n",
+ " model=model,\n",
+ " tokenizer=processor.tokenizer,\n",
+ " feature_extractor=processor.feature_extractor,\n",
+ " max_new_tokens=225,\n",
+ " chunk_length_s=30,\n",
+ " batch_size=16,\n",
+ " return_timestamps=False,\n",
+ " torch_dtype=torch_dtype,\n",
+ " device=device,\n",
+ " )\n",
+ "\n",
+ " clear_output()\n",
+ "\n",
+ " display(widgets.HTML(\n",
+ " value=\"Notiek audio atpazīšana...
\"\n",
+ " ))\n",
+ "\n",
+ " result = pipe(uploader.data[0])\n",
+ "\n",
+ " with open('transcript.txt', 'w') as f:\n",
+ " f.write(result[\"text\"])\n",
+ "\n",
+ " result_widget = widgets.HTML(\n",
+ " value=result[\"text\"]\n",
+ " )\n",
+ "\n",
+ " clear_output()\n",
+ "\n",
+ " display(widgets.HTML(\n",
+ " value=result[\"text\"]\n",
+ " ))"
+ ],
+ "metadata": {
+ "cellView": "form",
+ "id": "_6ovCwwqC6SM"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## 5. Saglabājiet audio failā atpazīto tekstu\n",
+ "Pēc audio faila apstrādes tajā atpazītais teksts tiks izdrukāts zem ceturtā soļa šūnas, kā arī tas tiks saglabāts teksta failā `transcript.txt`. Lai apskatītu šo failu uzklikšķiniet uz mapītes ikonas ekrāna sānā.\n",
+ "\n",
+ "\n"
+ ],
+ "metadata": {
+ "id": "PLqlD2N7STNq"
+ }
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3",
+ "name": "python3"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
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