diff --git a/notebooks/bark_demo_srt_audio.ipynb b/notebooks/bark_demo_srt_audio.ipynb
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "-4jTuaSA1By6",
+ "outputId": "8e417d1e-e69c-46a7-e0b1-a6895b04f64f"
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Collecting git+https://github.com/jayeshthk/bark.git\n",
+ " Cloning https://github.com/jayeshthk/bark.git to /tmp/pip-req-build-uffja7tb\n",
+ " Running command git clone --filter=blob:none --quiet https://github.com/jayeshthk/bark.git /tmp/pip-req-build-uffja7tb\n",
+ " Resolved https://github.com/jayeshthk/bark.git to commit 95977fb20b24ff29f479f9055ad52b0e56e9c634\n",
+ " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
+ " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
+ " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+ "Collecting boto3 (from suno-bark==0.0.1a0)\n",
+ " Downloading boto3-1.36.26-py3-none-any.whl.metadata (6.7 kB)\n",
+ "Collecting encodec (from suno-bark==0.0.1a0)\n",
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+ "\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+ "Collecting funcy (from suno-bark==0.0.1a0)\n",
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+ "Collecting pydub (from suno-bark==0.0.1a0)\n",
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+ "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (24.2)\n",
+ "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (6.0.2)\n",
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+ "Collecting botocore<1.37.0,>=1.36.26 (from boto3->suno-bark==0.0.1a0)\n",
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+ "\u001b[?25hBuilding wheels for collected packages: suno-bark, encodec\n",
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+ "Installing collected packages: pydub, funcy, nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, jmespath, nvidia-cusparse-cu12, nvidia-cudnn-cu12, botocore, s3transfer, nvidia-cusolver-cu12, boto3, encodec, suno-bark\n",
+ " Attempting uninstall: nvidia-nvjitlink-cu12\n",
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+ " Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n",
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+ " Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n",
+ " Attempting uninstall: nvidia-cuda-cupti-cu12\n",
+ " Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n",
+ " Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n",
+ " Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n",
+ " Attempting uninstall: nvidia-cublas-cu12\n",
+ " Found existing installation: nvidia-cublas-cu12 12.5.3.2\n",
+ " Uninstalling nvidia-cublas-cu12-12.5.3.2:\n",
+ " Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n",
+ " Attempting uninstall: nvidia-cusparse-cu12\n",
+ " Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n",
+ " Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n",
+ " Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n",
+ " Attempting uninstall: nvidia-cudnn-cu12\n",
+ " Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n",
+ " Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n",
+ " Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n",
+ " Attempting uninstall: nvidia-cusolver-cu12\n",
+ " Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n",
+ " Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n",
+ " Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n",
+ "Successfully installed boto3-1.36.26 botocore-1.36.26 encodec-0.1.1 funcy-2.0 jmespath-1.0.1 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127 pydub-0.25.1 s3transfer-0.11.2 suno-bark-0.0.1a0\n"
+ ]
+ }
+ ],
+ "source": [
+ "!pip install git+https://github.com/jayeshthk/bark.git"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
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+ "height": 1000,
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+ ]
+ },
+ "id": "2_pi0y6D1SaH",
+ "outputId": "631f417a-6bdb-4819-fcf0-dc67665f56bf"
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
+ "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
+ "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
+ "You will be able to reuse this secret in all of your notebooks.\n",
+ "Please note that authentication is recommended but still optional to access public models or datasets.\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "7dd5a75f180a48c68731494e10f5ed41",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "text_2.pt: 0%| | 0.00/5.35G [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/usr/local/lib/python3.11/dist-packages/bark/generation.py:212: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+ " checkpoint = torch.load(ckpt_path, map_location=device)\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "ce67143299434d45a893b832a1e99c80",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "tokenizer_config.json: 0%| | 0.00/49.0 [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "cf3408e339a64792952a07c1948b4fdc",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "248acbc74d254b4b9d095efc02309e58",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
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+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "47bcf8f33ccc42a4b5a423604250dda2",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "coarse_2.pt: 0%| | 0.00/3.93G [00:00, ?B/s]"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/usr/local/lib/python3.11/dist-packages/bark/generation.py:212: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+ " checkpoint = torch.load(ckpt_path, map_location=device)\n"
+ ]
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "31c9c918e0a94c0a8e0af5bd722dba68",
+ "version_major": 2,
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+ },
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+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/usr/local/lib/python3.11/dist-packages/torch/nn/utils/weight_norm.py:143: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.\n",
+ " WeightNorm.apply(module, name, dim)\n",
+ "Downloading: \"https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th\" to /root/.cache/torch/hub/checkpoints/encodec_24khz-d7cc33bc.th\n",
+ "100%|██████████| 88.9M/88.9M [00:01<00:00, 61.3MB/s]\n",
+ "Generating Audio: 0%| | 0/6 [00:00, ?it/s]/usr/local/lib/python3.11/dist-packages/bark/generation.py:175: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.\n",
+ " with InferenceContext(), torch.inference_mode(), torch.no_grad(), autocast():\n",
+ "\n",
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+ " 29%|██▉ | 224/768 [00:04<00:11, 48.83it/s]\u001b[A\n",
+ " 30%|██▉ | 230/768 [00:05<00:10, 50.72it/s]\u001b[A\n",
+ " 31%|███ | 236/768 [00:05<00:10, 52.40it/s]\u001b[A\n",
+ " 32%|███▏ | 242/768 [00:05<00:09, 52.89it/s]\u001b[A\n",
+ " 32%|███▏ | 248/768 [00:05<00:09, 53.71it/s]\u001b[A\n",
+ " 33%|███▎ | 254/768 [00:05<00:09, 54.21it/s]\u001b[A\n",
+ " 34%|███▍ | 260/768 [00:05<00:10, 50.72it/s]\u001b[A\n",
+ " 35%|███▍ | 266/768 [00:05<00:09, 52.04it/s]\u001b[A\n",
+ " 35%|███▌ | 272/768 [00:05<00:10, 49.37it/s]\u001b[A\n",
+ "100%|██████████| 272/272 [00:05<00:00, 46.04it/s]\n",
+ "\n",
+ " 0%| | 0/14 [00:00, ?it/s]\u001b[A\n",
+ " 7%|▋ | 1/14 [00:01<00:17, 1.33s/it]\u001b[A\n",
+ " 14%|█▍ | 2/14 [00:02<00:16, 1.38s/it]\u001b[A\n",
+ " 21%|██▏ | 3/14 [00:04<00:14, 1.35s/it]\u001b[A\n",
+ " 29%|██▊ | 4/14 [00:05<00:13, 1.33s/it]\u001b[A\n",
+ " 36%|███▌ | 5/14 [00:06<00:11, 1.32s/it]\u001b[A\n",
+ " 43%|████▎ | 6/14 [00:07<00:10, 1.32s/it]\u001b[A\n",
+ " 50%|█████ | 7/14 [00:09<00:09, 1.43s/it]\u001b[A\n",
+ " 57%|█████▋ | 8/14 [00:11<00:08, 1.44s/it]\u001b[A\n",
+ " 64%|██████▍ | 9/14 [00:12<00:07, 1.40s/it]\u001b[A\n",
+ " 71%|███████▏ | 10/14 [00:13<00:05, 1.36s/it]\u001b[A\n",
+ " 79%|███████▊ | 11/14 [00:15<00:04, 1.35s/it]\u001b[A\n",
+ " 86%|████████▌ | 12/14 [00:16<00:02, 1.34s/it]\u001b[A\n",
+ " 93%|█████████▎| 13/14 [00:17<00:01, 1.33s/it]\u001b[A\n",
+ "100%|██████████| 14/14 [00:18<00:00, 1.32s/it]\n",
+ "Generating Audio: 33%|███▎ | 2/6 [00:44<01:32, 23.18s/it]\n",
+ " 0%| | 0/768 [00:00, ?it/s]\u001b[A\n",
+ " 0%| | 1/768 [00:00<01:22, 9.30it/s]\u001b[A\n",
+ " 1%| | 5/768 [00:00<00:29, 25.59it/s]\u001b[A\n",
+ " 1%| | 9/768 [00:00<00:23, 31.73it/s]\u001b[A\n",
+ " 2%|▏ | 14/768 [00:00<00:20, 36.03it/s]\u001b[A\n",
+ " 2%|▏ | 18/768 [00:00<00:20, 36.00it/s]\u001b[A\n",
+ " 3%|▎ | 23/768 [00:00<00:19, 37.93it/s]\u001b[A\n",
+ " 4%|▎ | 28/768 [00:00<00:18, 40.13it/s]\u001b[A\n",
+ " 4%|▍ | 33/768 [00:00<00:17, 41.35it/s]\u001b[A\n",
+ " 5%|▍ | 38/768 [00:01<00:17, 40.89it/s]\u001b[A\n",
+ " 6%|▌ | 43/768 [00:01<00:19, 36.41it/s]\u001b[A\n",
+ " 6%|▌ | 47/768 [00:01<00:19, 36.61it/s]\u001b[A\n",
+ " 7%|▋ | 51/768 [00:01<00:19, 37.17it/s]\u001b[A\n",
+ " 7%|▋ | 55/768 [00:01<00:19, 36.41it/s]\u001b[A\n",
+ " 8%|▊ | 59/768 [00:01<00:19, 36.65it/s]\u001b[A\n",
+ " 8%|▊ | 63/768 [00:01<00:19, 35.56it/s]\u001b[A\n",
+ " 9%|▊ | 67/768 [00:01<00:19, 36.40it/s]\u001b[A\n",
+ " 10%|▉ | 73/768 [00:01<00:16, 41.27it/s]\u001b[A\n",
+ " 10%|█ | 78/768 [00:02<00:16, 42.03it/s]\u001b[A\n",
+ " 11%|█ | 83/768 [00:02<00:15, 43.03it/s]\u001b[A\n",
+ " 12%|█▏ | 89/768 [00:02<00:14, 46.38it/s]\u001b[A\n",
+ " 12%|█▏ | 95/768 [00:02<00:13, 49.67it/s]\u001b[A\n",
+ " 13%|█▎ | 101/768 [00:02<00:12, 51.87it/s]\u001b[A\n",
+ " 14%|█▍ | 107/768 [00:02<00:12, 52.46it/s]\u001b[A\n",
+ " 15%|█▍ | 113/768 [00:02<00:12, 53.76it/s]\u001b[A\n",
+ " 15%|█▌ | 119/768 [00:02<00:11, 54.59it/s]\u001b[A\n",
+ "100%|██████████| 121/121 [00:02<00:00, 42.17it/s]\n",
+ "\n",
+ " 0%| | 0/7 [00:00, ?it/s]\u001b[A\n",
+ " 14%|█▍ | 1/7 [00:01<00:07, 1.31s/it]\u001b[A\n",
+ " 29%|██▊ | 2/7 [00:02<00:06, 1.31s/it]\u001b[A\n",
+ " 43%|████▎ | 3/7 [00:03<00:05, 1.31s/it]\u001b[A\n",
+ " 57%|█████▋ | 4/7 [00:05<00:03, 1.32s/it]\u001b[A\n",
+ " 71%|███████▏ | 5/7 [00:06<00:02, 1.32s/it]\u001b[A\n",
+ " 86%|████████▌ | 6/7 [00:07<00:01, 1.32s/it]\u001b[A\n",
+ "100%|██████████| 7/7 [00:08<00:00, 1.17s/it]\n",
+ "Generating Audio: 50%|█████ | 3/6 [00:58<00:55, 18.62s/it]\n",
+ " 0%| | 0/768 [00:00, ?it/s]\u001b[A\n",
+ " 0%| | 1/768 [00:00<01:29, 8.61it/s]\u001b[A\n",
+ " 1%| | 5/768 [00:00<00:30, 25.27it/s]\u001b[A\n",
+ " 1%| | 9/768 [00:00<00:26, 28.70it/s]\u001b[A\n",
+ " 2%|▏ | 13/768 [00:00<00:23, 31.82it/s]\u001b[A\n",
+ " 2%|▏ | 17/768 [00:00<00:23, 32.20it/s]\u001b[A\n",
+ " 3%|▎ | 21/768 [00:00<00:22, 33.05it/s]\u001b[A\n",
+ " 4%|▎ | 27/768 [00:00<00:18, 39.95it/s]\u001b[A\n",
+ " 4%|▍ | 32/768 [00:00<00:17, 42.34it/s]\u001b[A\n",
+ " 5%|▍ | 37/768 [00:01<00:16, 43.95it/s]\u001b[A\n",
+ " 6%|▌ | 43/768 [00:01<00:15, 47.63it/s]\u001b[A\n",
+ " 6%|▋ | 48/768 [00:01<00:14, 48.22it/s]\u001b[A\n",
+ " 7%|▋ | 54/768 [00:01<00:14, 50.95it/s]\u001b[A\n",
+ " 8%|▊ | 60/768 [00:01<00:13, 52.80it/s]\u001b[A\n",
+ " 9%|▊ | 66/768 [00:01<00:12, 54.10it/s]\u001b[A\n",
+ " 9%|▉ | 72/768 [00:01<00:12, 55.11it/s]\u001b[A\n",
+ " 10%|█ | 78/768 [00:01<00:12, 55.31it/s]\u001b[A\n",
+ " 11%|█ | 84/768 [00:01<00:12, 55.26it/s]\u001b[A\n",
+ " 12%|█▏ | 90/768 [00:01<00:13, 50.42it/s]\u001b[A\n",
+ " 12%|█▎ | 96/768 [00:02<00:13, 51.40it/s]\u001b[A\n",
+ " 13%|█▎ | 102/768 [00:02<00:12, 51.25it/s]\u001b[A\n",
+ " 14%|█▍ | 108/768 [00:02<00:12, 52.01it/s]\u001b[A\n",
+ " 15%|█▍ | 114/768 [00:02<00:12, 53.16it/s]\u001b[A\n",
+ " 16%|█▌ | 120/768 [00:02<00:11, 54.04it/s]\u001b[A\n",
+ " 16%|█▋ | 126/768 [00:02<00:11, 54.42it/s]\u001b[A\n",
+ " 17%|█▋ | 132/768 [00:02<00:11, 54.12it/s]\u001b[A\n",
+ " 18%|█▊ | 138/768 [00:02<00:11, 53.18it/s]\u001b[A\n",
+ " 19%|█▉ | 144/768 [00:03<00:12, 51.19it/s]\u001b[A\n",
+ " 20%|█▉ | 150/768 [00:03<00:11, 51.80it/s]\u001b[A\n",
+ "100%|██████████| 150/150 [00:03<00:00, 47.89it/s]\n",
+ "\n",
+ " 0%| | 0/8 [00:00, ?it/s]\u001b[A\n",
+ " 12%|█▎ | 1/8 [00:01<00:09, 1.36s/it]\u001b[A\n",
+ " 25%|██▌ | 2/8 [00:02<00:08, 1.33s/it]\u001b[A\n",
+ " 38%|███▊ | 3/8 [00:03<00:06, 1.32s/it]\u001b[A\n",
+ " 50%|█████ | 4/8 [00:05<00:05, 1.32s/it]\u001b[A\n",
+ " 62%|██████▎ | 5/8 [00:06<00:03, 1.31s/it]\u001b[A\n",
+ " 75%|███████▌ | 6/8 [00:08<00:02, 1.37s/it]\u001b[A\n",
+ " 88%|████████▊ | 7/8 [00:09<00:01, 1.46s/it]\u001b[A\n",
+ "100%|██████████| 8/8 [00:10<00:00, 1.32s/it]\n",
+ "Generating Audio: 67%|██████▋ | 4/6 [01:13<00:34, 17.49s/it]\n",
+ " 0%| | 0/768 [00:00, ?it/s]\u001b[A\n",
+ " 0%| | 1/768 [00:00<01:18, 9.80it/s]\u001b[A\n",
+ " 1%| | 6/768 [00:00<00:23, 32.88it/s]\u001b[A\n",
+ " 2%|▏ | 12/768 [00:00<00:17, 43.75it/s]\u001b[A\n",
+ " 2%|▏ | 18/768 [00:00<00:16, 46.83it/s]\u001b[A\n",
+ " 3%|▎ | 24/768 [00:00<00:14, 49.95it/s]\u001b[A\n",
+ " 4%|▍ | 30/768 [00:00<00:14, 52.20it/s]\u001b[A\n",
+ " 5%|▍ | 36/768 [00:00<00:14, 52.15it/s]\u001b[A\n",
+ " 5%|▌ | 42/768 [00:00<00:14, 51.83it/s]\u001b[A\n",
+ " 6%|▋ | 48/768 [00:00<00:13, 52.62it/s]\u001b[A\n",
+ " 7%|▋ | 54/768 [00:01<00:13, 53.93it/s]\u001b[A\n",
+ " 8%|▊ | 60/768 [00:01<00:14, 50.02it/s]\u001b[A\n",
+ " 9%|▊ | 66/768 [00:01<00:13, 51.75it/s]\u001b[A\n",
+ " 9%|▉ | 72/768 [00:01<00:13, 52.19it/s]\u001b[A\n",
+ " 10%|█ | 78/768 [00:01<00:13, 52.75it/s]\u001b[A\n",
+ " 11%|█ | 84/768 [00:01<00:12, 53.45it/s]\u001b[A\n",
+ " 12%|█▏ | 90/768 [00:01<00:12, 53.32it/s]\u001b[A\n",
+ " 12%|█▎ | 96/768 [00:01<00:12, 52.50it/s]\u001b[A\n",
+ " 13%|█▎ | 102/768 [00:02<00:12, 53.22it/s]\u001b[A\n",
+ " 14%|█▍ | 108/768 [00:02<00:12, 52.56it/s]\u001b[A\n",
+ " 15%|█▍ | 114/768 [00:02<00:13, 49.85it/s]\u001b[A\n",
+ " 16%|█▌ | 120/768 [00:02<00:12, 51.14it/s]\u001b[A\n",
+ " 16%|█▋ | 126/768 [00:02<00:12, 50.20it/s]\u001b[A\n",
+ " 17%|█▋ | 132/768 [00:02<00:12, 51.04it/s]\u001b[A\n",
+ " 18%|█▊ | 138/768 [00:02<00:12, 51.32it/s]\u001b[A\n",
+ " 19%|█▉ | 144/768 [00:02<00:12, 51.50it/s]\u001b[A\n",
+ " 20%|█▉ | 150/768 [00:02<00:12, 51.40it/s]\u001b[A\n",
+ " 20%|██ | 156/768 [00:03<00:11, 52.47it/s]\u001b[A\n",
+ " 21%|██ | 162/768 [00:03<00:12, 49.17it/s]\u001b[A\n",
+ " 22%|██▏ | 168/768 [00:03<00:11, 50.49it/s]\u001b[A\n",
+ " 23%|██▎ | 174/768 [00:03<00:11, 51.86it/s]\u001b[A\n",
+ "100%|██████████| 175/175 [00:03<00:00, 50.68it/s]\n",
+ "\n",
+ " 0%| | 0/9 [00:00, ?it/s]\u001b[A\n",
+ " 11%|█ | 1/9 [00:01<00:10, 1.33s/it]\u001b[A\n",
+ " 22%|██▏ | 2/9 [00:02<00:09, 1.32s/it]\u001b[A\n",
+ " 33%|███▎ | 3/9 [00:04<00:08, 1.42s/it]\u001b[A\n",
+ " 44%|████▍ | 4/9 [00:05<00:07, 1.50s/it]\u001b[A\n",
+ " 56%|█████▌ | 5/9 [00:07<00:05, 1.44s/it]\u001b[A\n",
+ " 67%|██████▋ | 6/9 [00:08<00:04, 1.41s/it]\u001b[A\n",
+ " 78%|███████▊ | 7/9 [00:09<00:02, 1.37s/it]\u001b[A\n",
+ " 89%|████████▉ | 8/9 [00:11<00:01, 1.36s/it]\u001b[A\n",
+ "100%|██████████| 9/9 [00:12<00:00, 1.36s/it]\n",
+ "Generating Audio: 83%|████████▎ | 5/6 [01:31<00:17, 17.57s/it]\n",
+ " 0%| | 0/768 [00:00, ?it/s]\u001b[A\n",
+ " 0%| | 1/768 [00:00<01:17, 9.86it/s]\u001b[A\n",
+ " 1%| | 7/768 [00:00<00:20, 37.42it/s]\u001b[A\n",
+ " 2%|▏ | 13/768 [00:00<00:16, 45.38it/s]\u001b[A\n",
+ " 2%|▏ | 19/768 [00:00<00:16, 46.67it/s]\u001b[A\n",
+ " 3%|▎ | 25/768 [00:00<00:14, 49.83it/s]\u001b[A\n",
+ " 4%|▍ | 30/768 [00:00<00:15, 49.12it/s]\u001b[A\n",
+ " 5%|▍ | 36/768 [00:00<00:14, 50.12it/s]\u001b[A\n",
+ " 5%|▌ | 42/768 [00:00<00:13, 51.97it/s]\u001b[A\n",
+ " 6%|▋ | 48/768 [00:00<00:13, 53.23it/s]\u001b[A\n",
+ " 7%|▋ | 54/768 [00:01<00:13, 53.77it/s]\u001b[A\n",
+ " 8%|▊ | 60/768 [00:01<00:15, 46.72it/s]\u001b[A\n",
+ " 8%|▊ | 65/768 [00:01<00:16, 43.18it/s]\u001b[A\n",
+ " 9%|▉ | 70/768 [00:01<00:16, 41.19it/s]\u001b[A\n",
+ " 10%|▉ | 75/768 [00:01<00:17, 39.54it/s]\u001b[A\n",
+ " 10%|█ | 80/768 [00:01<00:17, 39.30it/s]\u001b[A\n",
+ " 11%|█ | 85/768 [00:01<00:17, 38.59it/s]\u001b[A\n",
+ " 12%|█▏ | 89/768 [00:02<00:17, 38.46it/s]\u001b[A\n",
+ " 12%|█▏ | 94/768 [00:02<00:16, 39.82it/s]\u001b[A\n",
+ " 13%|█▎ | 99/768 [00:02<00:16, 40.93it/s]\u001b[A\n",
+ " 14%|█▎ | 104/768 [00:02<00:15, 41.73it/s]\u001b[A\n",
+ " 14%|█▍ | 109/768 [00:02<00:17, 38.03it/s]\u001b[A\n",
+ " 15%|█▍ | 113/768 [00:02<00:17, 37.13it/s]\u001b[A\n",
+ " 15%|█▌ | 117/768 [00:02<00:17, 36.82it/s]\u001b[A\n",
+ " 16%|█▌ | 121/768 [00:02<00:18, 35.63it/s]\u001b[A\n",
+ " 16%|█▋ | 125/768 [00:03<00:17, 35.75it/s]\u001b[A\n",
+ " 17%|█▋ | 129/768 [00:03<00:18, 35.01it/s]\u001b[A\n",
+ " 17%|█▋ | 133/768 [00:03<00:17, 35.47it/s]\u001b[A\n",
+ " 18%|█▊ | 139/768 [00:03<00:15, 40.94it/s]\u001b[A\n",
+ " 19%|█▉ | 144/768 [00:03<00:14, 42.01it/s]\u001b[A\n",
+ " 19%|█▉ | 149/768 [00:03<00:14, 43.59it/s]\u001b[A\n",
+ " 20%|██ | 155/768 [00:03<00:13, 46.90it/s]\u001b[A\n",
+ " 21%|██ | 160/768 [00:03<00:12, 47.71it/s]\u001b[A\n",
+ " 22%|██▏ | 166/768 [00:03<00:12, 50.04it/s]\u001b[A\n",
+ " 22%|██▏ | 172/768 [00:03<00:11, 51.12it/s]\u001b[A\n",
+ " 23%|██▎ | 178/768 [00:04<00:11, 50.05it/s]\u001b[A\n",
+ " 24%|██▍ | 184/768 [00:04<00:11, 50.94it/s]\u001b[A\n",
+ " 25%|██▍ | 190/768 [00:04<00:11, 50.83it/s]\u001b[A\n",
+ " 26%|██▌ | 196/768 [00:04<00:11, 48.69it/s]\u001b[A\n",
+ " 26%|██▋ | 202/768 [00:04<00:11, 50.78it/s]\u001b[A\n",
+ " 27%|██▋ | 208/768 [00:04<00:10, 52.50it/s]\u001b[A\n",
+ " 28%|██▊ | 214/768 [00:04<00:10, 51.99it/s]\u001b[A\n",
+ " 29%|██▊ | 220/768 [00:04<00:10, 52.59it/s]\u001b[A\n",
+ " 29%|██▉ | 226/768 [00:05<00:10, 53.55it/s]\u001b[A\n",
+ " 30%|███ | 232/768 [00:05<00:10, 52.65it/s]\u001b[A\n",
+ " 31%|███ | 238/768 [00:05<00:09, 53.17it/s]\u001b[A\n",
+ " 32%|███▏ | 244/768 [00:05<00:09, 53.52it/s]\u001b[A\n",
+ " 33%|███▎ | 250/768 [00:05<00:10, 49.63it/s]\u001b[A\n",
+ " 33%|███▎ | 256/768 [00:05<00:09, 51.40it/s]\u001b[A\n",
+ " 34%|███▍ | 262/768 [00:05<00:09, 52.43it/s]\u001b[A\n",
+ " 35%|███▍ | 268/768 [00:05<00:09, 51.48it/s]\u001b[A\n",
+ " 36%|███▌ | 274/768 [00:05<00:09, 52.60it/s]\u001b[A\n",
+ " 36%|███▋ | 280/768 [00:06<00:09, 53.72it/s]\u001b[A\n",
+ " 37%|███▋ | 286/768 [00:06<00:08, 54.33it/s]\u001b[A\n",
+ " 38%|███▊ | 292/768 [00:06<00:08, 54.27it/s]\u001b[A\n",
+ " 39%|███▉ | 298/768 [00:06<00:08, 54.34it/s]\u001b[A\n",
+ " 40%|███▉ | 304/768 [00:06<00:09, 50.06it/s]\u001b[A\n",
+ " 40%|████ | 310/768 [00:06<00:08, 51.50it/s]\u001b[A\n",
+ " 41%|████ | 316/768 [00:06<00:08, 52.27it/s]\u001b[A\n",
+ " 42%|████▏ | 322/768 [00:06<00:08, 51.50it/s]\u001b[A\n",
+ " 43%|████▎ | 328/768 [00:06<00:08, 52.77it/s]\u001b[A\n",
+ " 43%|████▎ | 334/768 [00:07<00:08, 53.35it/s]\u001b[A\n",
+ " 44%|████▍ | 340/768 [00:07<00:08, 53.38it/s]\u001b[A\n",
+ " 45%|████▌ | 346/768 [00:07<00:07, 53.45it/s]\u001b[A\n",
+ " 46%|████▌ | 352/768 [00:07<00:08, 51.59it/s]\u001b[A\n",
+ " 47%|████▋ | 358/768 [00:07<00:08, 50.43it/s]\u001b[A\n",
+ " 47%|████▋ | 364/768 [00:07<00:07, 51.58it/s]\u001b[A\n",
+ " 48%|████▊ | 370/768 [00:07<00:07, 50.52it/s]\u001b[A\n",
+ " 49%|████▉ | 376/768 [00:07<00:07, 49.84it/s]\u001b[A\n",
+ "100%|██████████| 377/377 [00:07<00:00, 47.41it/s]\n",
+ "\n",
+ " 0%| | 0/19 [00:00, ?it/s]\u001b[A\n",
+ " 5%|▌ | 1/19 [00:01<00:23, 1.32s/it]\u001b[A\n",
+ " 11%|█ | 2/19 [00:02<00:22, 1.32s/it]\u001b[A\n",
+ " 16%|█▌ | 3/19 [00:03<00:20, 1.31s/it]\u001b[A\n",
+ " 21%|██ | 4/19 [00:05<00:19, 1.31s/it]\u001b[A\n",
+ " 26%|██▋ | 5/19 [00:06<00:20, 1.45s/it]\u001b[A\n",
+ " 32%|███▏ | 6/19 [00:08<00:18, 1.40s/it]\u001b[A\n",
+ " 37%|███▋ | 7/19 [00:09<00:16, 1.37s/it]\u001b[A\n",
+ " 42%|████▏ | 8/19 [00:10<00:14, 1.35s/it]\u001b[A\n",
+ " 47%|████▋ | 9/19 [00:12<00:13, 1.33s/it]\u001b[A\n",
+ " 53%|█████▎ | 10/19 [00:13<00:11, 1.33s/it]\u001b[A\n",
+ " 58%|█████▊ | 11/19 [00:14<00:10, 1.32s/it]\u001b[A\n",
+ " 63%|██████▎ | 12/19 [00:16<00:09, 1.32s/it]\u001b[A\n",
+ " 68%|██████▊ | 13/19 [00:17<00:08, 1.36s/it]\u001b[A\n",
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+ " 79%|███████▉ | 15/19 [00:20<00:05, 1.41s/it]\u001b[A\n",
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+ " 89%|████████▉ | 17/19 [00:23<00:02, 1.36s/it]\u001b[A\n",
+ " 95%|█████████▍| 18/19 [00:24<00:01, 1.35s/it]\u001b[A\n",
+ "100%|██████████| 19/19 [00:25<00:00, 1.35s/it]\n",
+ "Generating Audio: 100%|██████████| 6/6 [02:09<00:00, 21.54s/it]"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "✅ Saved final part: sample_data/output_part_1.wav\n",
+ "🎉 Audio generation complete!\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "from bark import srt_to_audio\n",
+ "\n",
+ "# Path to your SRT file\n",
+ "\n",
+ "# Generate audio from SRT\n",
+ "audio_array = srt_to_audio(\n",
+ " srt_file_path=\"data/subtitle.srt\", # Path to your SRT file\n",
+ " output_dir=\"sample_data/\" # Output directory\n",
+ ")"
+ ]
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+ "import IPython.display as ipd\n",
+ "import librosa\n",
+ "\n",
+ "# Replace 'your_audio_file.wav' with the actual path to your WAV file\n",
+ "audio_file_path = '/content/sample_data/output_part_1.wav'\n",
+ "\n",
+ "try:\n",
+ " # Load the audio file using librosa\n",
+ " audio_data, sample_rate = librosa.load(audio_file_path)\n",
+ "\n",
+ " # Play the audio using IPython.display.Audio\n",
+ " ipd.Audio(audio_data, rate=sample_rate)\n",
+ "\n",
+ "except FileNotFoundError:\n",
+ " print(f\"Error: Audio file not found at {audio_file_path}\")\n",
+ "except Exception as e:\n",
+ " print(f\"An error occurred: {e}\")\n"
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diff --git a/notebooks/data/subtitle.srt b/notebooks/data/subtitle.srt
new file mode 100644
index 0000000..4d2a4b2
--- /dev/null
+++ b/notebooks/data/subtitle.srt
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+1
+00:00:01,599 --> 00:00:06,600
+Hello and welcome to CubicIn and this
+
+2
+00:00:06,600 --> 00:00:10,599
+platform helps students and teachers in
+
+3
+00:00:10,599 --> 00:00:12,440
+making quizzes.
+
+4
+00:00:12,440 --> 00:00:16,800
+This quiz is AI based, so it is
+
+5
+00:00:16,800 --> 00:00:20,199
+unique every time and it
+
+6
+00:00:20,199 --> 00:00:24,240
+basically makes quizzes by following the structure of the syllabus and government and or