{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyN//kAorUssjRtRjm/BIpc2"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"PTphXgZv5PxK","executionInfo":{"status":"ok","timestamp":1684901181065,"user_tz":-330,"elapsed":23218,"user":{"displayName":"Sulakshana Geeth","userId":"14781868669328079827"}},"outputId":"cd2eee86-b161-4a03-bf06-c41f1804155b"},"outputs":[{"output_type":"stream","name":"stdout","text":["Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.0.1+cu118)\n","Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.29.2)\n","Requirement already satisfied: gradio in 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in /usr/local/lib/python3.10/dist-packages (from transformers) (4.65.0)\n","Requirement already satisfied: aiofiles in /usr/local/lib/python3.10/dist-packages (from gradio) (23.1.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from gradio) (3.8.4)\n","Requirement already satisfied: altair>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n","Requirement already satisfied: fastapi in /usr/local/lib/python3.10/dist-packages (from gradio) (0.95.2)\n","Requirement already satisfied: ffmpy in /usr/local/lib/python3.10/dist-packages (from gradio) (0.3.0)\n","Requirement already satisfied: gradio-client>=0.2.4 in /usr/local/lib/python3.10/dist-packages (from gradio) (0.2.5)\n","Requirement already satisfied: httpx in /usr/local/lib/python3.10/dist-packages (from gradio) (0.24.1)\n","Requirement already satisfied: markdown-it-py[linkify]>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (2.2.0)\n","Requirement 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(2022.12.7)\n","Requirement already satisfied: httpcore<0.18.0,>=0.15.0 in /usr/local/lib/python3.10/dist-packages (from httpx->gradio) (0.17.2)\n","Requirement already satisfied: idna in /usr/local/lib/python3.10/dist-packages (from httpx->gradio) (3.4)\n","Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from httpx->gradio) (1.3.0)\n","Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->gradio) (1.0.7)\n","Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib->gradio) (0.11.0)\n","Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib->gradio) (4.39.3)\n","Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->gradio) (1.4.4)\n","Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib->gradio) (3.0.9)\n","Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.15)\n","Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch) (1.3.0)\n","Requirement already satisfied: anyio<5.0,>=3.0 in /usr/local/lib/python3.10/dist-packages (from httpcore<0.18.0,>=0.15.0->httpx->gradio) (3.6.2)\n","Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair>=4.2.0->gradio) (0.19.3)\n","Requirement already satisfied: uc-micro-py in /usr/local/lib/python3.10/dist-packages (from linkify-it-py<3,>=1->markdown-it-py[linkify]>=2.0.0->gradio) (1.0.2)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->gradio) (1.16.0)\n"]},{"output_type":"stream","name":"stderr","text":["Some weights of the model checkpoint at jonatasgrosman/wav2vec2-large-xlsr-53-english were not used when initializing Wav2Vec2ForSequenceClassification: ['lm_head.bias', 'lm_head.weight']\n","- This IS expected if you are initializing Wav2Vec2ForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n","- This IS NOT expected if you are initializing Wav2Vec2ForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n","Some weights of Wav2Vec2ForSequenceClassification were not initialized from the model checkpoint at jonatasgrosman/wav2vec2-large-xlsr-53-english and are newly initialized: ['projector.bias', 'projector.weight', 'classifier.bias', 'classifier.weight']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n","/usr/local/lib/python3.10/dist-packages/gradio/inputs.py:321: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n"," warnings.warn(\n","/usr/local/lib/python3.10/dist-packages/gradio/inputs.py:324: UserWarning: `optional` parameter is deprecated, and it has no effect\n"," super().__init__(source=source, type=type, label=label, optional=optional)\n","/usr/local/lib/python3.10/dist-packages/gradio/outputs.py:22: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n"," warnings.warn(\n"]},{"output_type":"stream","name":"stdout","text":["Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n","Note: opening Chrome Inspector may crash demo inside Colab notebooks.\n","\n","To create a public link, set `share=True` in `launch()`.\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.Javascript object>"],"application/javascript":["(async (port, path, width, height, cache, element) => {\n"," if (!google.colab.kernel.accessAllowed && !cache) {\n"," return;\n"," }\n"," element.appendChild(document.createTextNode(''));\n"," const url = await google.colab.kernel.proxyPort(port, {cache});\n","\n"," const external_link = document.createElement('div');\n"," external_link.innerHTML = `\n"," <div style=\"font-family: monospace; margin-bottom: 0.5rem\">\n"," Running on <a href=${new URL(path, url).toString()} target=\"_blank\">\n"," https://localhost:${port}${path}\n"," </a>\n"," </div>\n"," `;\n"," element.appendChild(external_link);\n","\n"," const iframe = document.createElement('iframe');\n"," iframe.src = new URL(path, url).toString();\n"," iframe.height = height;\n"," iframe.allow = \"autoplay; camera; microphone; clipboard-read; clipboard-write;\"\n"," iframe.width = width;\n"," iframe.style.border = 0;\n"," element.appendChild(iframe);\n"," })(7861, \"/\", \"100%\", 500, false, window.element)"]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":[]},"metadata":{},"execution_count":2}],"source":["!pip install torch transformers gradio torchaudio\n","\n","import torch\n","from transformers import Wav2Vec2Processor, Wav2Vec2ForSequenceClassification\n","import torchaudio\n","import numpy as np\n","import gradio as gr\n","\n","# Step 1: Define the speaking tone classification model\n","model_name = \"jonatasgrosman/wav2vec2-large-xlsr-53-english\"\n","processor = Wav2Vec2Processor.from_pretrained(model_name)\n","model = Wav2Vec2ForSequenceClassification.from_pretrained(model_name)\n","\n","# Step 2: Create a function to analyze the speaking tone\n","def analyze_speaking_tone(audio):\n"," try:\n"," waveform, sample_rate = torchaudio.load(audio)\n"," input_values = processor(waveform, return_tensors=\"pt\").input_values\n"," attention_mask = torch.ones_like(input_values)\n","\n"," with torch.no_grad():\n"," outputs = model(input_values=input_values, attention_mask=attention_mask)\n","\n"," predicted_label = torch.argmax(outputs.logits).item()\n"," if predicted_label == 1:\n"," speaking_tone = \"Abnormal\"\n"," else:\n"," speaking_tone = \"Normal\"\n","\n"," return speaking_tone\n"," except Exception as e:\n"," recommendation = \"An error occurred while analyzing the speaking tone. Please try the following steps:\\n\\n1. Ensure that the audio input is in a valid format.\\n2. Check the quality and clarity of the audio.\\n3. Adjust the preprocessing techniques such as noise reduction or audio normalization.\\n4. Retrain the speaking tone classification model using a diverse and high-quality audio dataset.\\n\\nIf the issue persists, please consult with a domain expert or seek technical support.\"\n"," return recommendation\n","\n","# Step 3: Create a Gradio interface to interact with the model\n","audio_input = gr.inputs.Audio(label=\"Audio\", type=\"numpy\")\n","tone_output = gr.outputs.Textbox(label=\"Speaking Tone\")\n","\n","iface = gr.Interface(fn=analyze_speaking_tone, inputs=audio_input, outputs=tone_output)\n","iface.launch()\n"]}]}
