rristo commited on
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1 Parent(s): 3996908

update example

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Files changed (1) hide show
  1. example_usage.ipynb +262 -36
example_usage.ipynb CHANGED
@@ -2,31 +2,24 @@
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  "cells": [
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  {
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  "cell_type": "code",
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- "execution_count": 1,
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  "id": "5920c653-448e-43b3-93eb-12d7073ad352",
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  "metadata": {
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  "tags": []
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  },
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- "outputs": [
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- {
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- "name": "stderr",
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- "output_type": "stream",
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- "text": [
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- "/opt/espnet/tools/anaconda/envs/espnet/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
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- " from .autonotebook import tqdm as notebook_tqdm\n"
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- ]
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- }
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- ],
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  "source": [
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- "from espnet2.bin.asr_inference import Speech2Text\n",
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- "from espnet2.bin.asr_align import CTCSegmentation\n",
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  "import soundfile\n",
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- "import pandas as pd"
 
 
 
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  ]
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 2,
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  "id": "83058587-1a8a-4b01-92ff-e9125fbe55a3",
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  "metadata": {
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  "tags": []
@@ -47,14 +40,15 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 3,
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  "id": "5e4670d6-0949-48cf-b6b1-d9cc4cf3ad65",
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  "metadata": {
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  "tags": []
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  },
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  "outputs": [],
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  "source": [
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- "speech2text = Speech2Text(\"exp/config.yaml\", \"exp/valid.acc.ave_10best.pth\", quantize_asr_model=True, quantize_lm=True)"
 
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  ]
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  },
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  {
@@ -69,7 +63,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 4,
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  "id": "e8120e8e-3718-4a1a-ab7a-46ef98a6bc11",
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  "metadata": {
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  "tags": []
@@ -82,7 +76,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 5,
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  "id": "eec8d4b2-c27a-4780-aeed-8aa7538f70e5",
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  "metadata": {
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  "tags": []
@@ -92,8 +86,8 @@
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  "name": "stdout",
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  "output_type": "stream",
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  "text": [
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- "CPU times: user 2.64 s, sys: 6.23 ms, total: 2.65 s\n",
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- "Wall time: 2.66 s\n"
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  ]
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  }
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  ],
@@ -103,7 +97,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 6,
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  "id": "39f41a8b-94c3-42d6-a989-6c7183a6f94d",
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  "metadata": {
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  "tags": []
@@ -123,7 +117,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 7,
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  "id": "812060a6-90de-4134-8d1f-9f3d98853bc2",
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  "metadata": {
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  "tags": []
@@ -224,7 +218,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 10,
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  "id": "ae9f7e3f-b75d-4bcb-98d1-ae2f037fb4af",
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  "metadata": {
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  "tags": []
@@ -244,7 +238,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 11,
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  "id": "0215d312-1896-43f1-9782-c92aced787b7",
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  "metadata": {
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  "tags": []
@@ -254,8 +248,8 @@
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  "name": "stdout",
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  "output_type": "stream",
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  "text": [
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- "CPU times: user 2.96 s, sys: 19 ms, total: 2.98 s\n",
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- "Wall time: 2.98 s\n"
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  ]
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  }
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  ],
@@ -268,7 +262,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 12,
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  "id": "d31d6840-3a80-411a-969c-05f4a5e3e9a1",
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  "metadata": {
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  "tags": []
@@ -506,20 +500,252 @@
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  ]
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  },
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  {
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- "cell_type": "code",
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- "execution_count": null,
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- "id": "7a4be2b1-5e0f-4558-8097-b37be0b83785",
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  "metadata": {},
 
 
 
 
 
 
 
 
 
 
 
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  "outputs": [],
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- "source": []
 
 
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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- "id": "1e9d45ad-c8fc-4bab-9285-b82ff3903702",
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- "metadata": {},
 
 
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  "outputs": [],
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- "source": []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  ],
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  "metadata": {
 
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  "cells": [
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  {
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  "cell_type": "code",
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+ "execution_count": 16,
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  "id": "5920c653-448e-43b3-93eb-12d7073ad352",
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  "metadata": {
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  "tags": []
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  },
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+ "outputs": [],
 
 
 
 
 
 
 
 
 
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  "source": [
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+ "import time\n",
 
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  "import soundfile\n",
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+ "import pandas as pd\n",
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+ "import matplotlib.pyplot as plt\n",
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+ "from espnet2.bin.asr_inference import Speech2Text\n",
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+ "from espnet2.bin.asr_align import CTCSegmentation"
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  ]
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 5,
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  "id": "83058587-1a8a-4b01-92ff-e9125fbe55a3",
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  "metadata": {
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  "tags": []
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 44,
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  "id": "5e4670d6-0949-48cf-b6b1-d9cc4cf3ad65",
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  "metadata": {
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  "tags": []
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  },
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  "outputs": [],
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  "source": [
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+ "#longer beam size take more time but is more accurate, default is 20\n",
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+ "speech2text = Speech2Text(\"exp/config.yaml\", \"exp/valid.acc.ave_10best.pth\", quantize_asr_model=True, quantize_lm=True, beam_size=10)"
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  ]
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  },
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  {
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 45,
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  "id": "e8120e8e-3718-4a1a-ab7a-46ef98a6bc11",
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  "metadata": {
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  "tags": []
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 46,
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  "id": "eec8d4b2-c27a-4780-aeed-8aa7538f70e5",
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  "metadata": {
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  "tags": []
 
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  "name": "stdout",
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  "output_type": "stream",
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  "text": [
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+ "CPU times: user 1.71 s, sys: 9.89 ms, total: 1.72 s\n",
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+ "Wall time: 1.75 s\n"
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  ]
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  }
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  ],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 47,
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  "id": "39f41a8b-94c3-42d6-a989-6c7183a6f94d",
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  "metadata": {
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  "tags": []
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 32,
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  "id": "812060a6-90de-4134-8d1f-9f3d98853bc2",
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  "metadata": {
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  "tags": []
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 25,
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  "id": "ae9f7e3f-b75d-4bcb-98d1-ae2f037fb4af",
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  "metadata": {
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  "tags": []
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 26,
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  "id": "0215d312-1896-43f1-9782-c92aced787b7",
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  "metadata": {
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  "tags": []
 
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  "name": "stdout",
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  "output_type": "stream",
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  "text": [
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+ "CPU times: user 1.68 s, sys: 0 ns, total: 1.68 s\n",
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+ "Wall time: 1.68 s\n"
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  ]
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  }
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  ],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 27,
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  "id": "d31d6840-3a80-411a-969c-05f4a5e3e9a1",
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  "metadata": {
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  "tags": []
 
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  ]
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  },
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  {
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+ "cell_type": "markdown",
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+ "id": "6288dbee-b84b-4465-829e-978352a9f0e7",
 
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  "metadata": {},
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+ "source": [
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+ "## Chunk audio to see how long audio increases transcripton time significantly"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "id": "6e7af387-d4bf-486e-a12a-9689242793fe",
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+ "metadata": {
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+ "tags": []
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+ },
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  "outputs": [],
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+ "source": [
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+ "from subprocess import Popen, PIPE"
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+ ]
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 7,
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+ "id": "0d51f384-4e1d-435f-993e-351af6bc42ff",
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+ "metadata": {
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+ "tags": []
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+ },
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  "outputs": [],
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+ "source": [
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+ "def chunk_audio(src_file, to_file, start, end):\n",
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+ " proc = Popen(['sox', src_file, to_file, 'trim', str(start), f'={end}'], stdout=PIPE, stderr=PIPE)\n",
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+ " stdout, stderr = proc.communicate()\n",
534
+ " return stdout, stderr\n",
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+ "\n",
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+ "from_file='example_audio/oden_kypsis16k.wav'\n",
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+ "to_files=[]\n",
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+ "for i in range(5, 31):\n",
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+ " to_file=f'example_audio/chunks/oden_kypsis16k_chunk_{i}.wav'\n",
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+ " chunk_audio(from_file, to_file, 0, i)\n",
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+ " to_files.append(to_file)"
542
+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 38,
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+ "id": "9aad1658-bdbc-479c-b1f9-89e52c6c2487",
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+ "metadata": {
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+ "tags": []
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+ },
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+ "outputs": [],
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+ "source": [
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+ "chunk_times=[]\n",
554
+ "for file in to_files:\n",
555
+ " speech, rate = soundfile.read(file)\n",
556
+ " assert rate == 16000\n",
557
+ " start=time.time()\n",
558
+ " text, *_ = speech2text(speech)\n",
559
+ " end=time.time()\n",
560
+ " duration=end-start\n",
561
+ " chunk_times.append([file, text[0], duration, len(speech)/16000])\n",
562
+ "df_chunk_times=pd.DataFrame(chunk_times)"
563
+ ]
564
+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 39,
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+ "id": "9d3cd39b-9199-493c-a4d9-4084c92d844a",
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+ "metadata": {
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+ "tags": []
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+ },
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [
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+ "<div>\n",
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+ "<style scoped>\n",
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+ " .dataframe tbody tr th:only-of-type {\n",
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+ " vertical-align: middle;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
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+ " }\n",
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+ "</style>\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
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+ " <thead>\n",
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+ " <tr style=\"text-align: right;\">\n",
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+ " <th></th>\n",
594
+ " <th>file</th>\n",
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+ " <th>hyp</th>\n",
596
+ " <th>elapsed_time</th>\n",
597
+ " <th>audio_dur_sec</th>\n",
598
+ " <th>trans_time_audio_dur_share</th>\n",
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+ " </tr>\n",
600
+ " </thead>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <th>0</th>\n",
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+ " <td>example_audio/chunks/oden_kypsis16k_chunk_5.wav</td>\n",
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+ " <td>enamus ajast nagu klik</td>\n",
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+ " <td>0.418611</td>\n",
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+ " <td>5.0</td>\n",
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+ " <td>0.083722</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>1</th>\n",
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+ " <td>example_audio/chunks/oden_kypsis16k_chunk_6.wav</td>\n",
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+ " <td>enamus ajast nagu klikid neid all</td>\n",
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+ " <td>0.481883</td>\n",
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+ " <td>6.0</td>\n",
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+ " <td>0.080314</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>2</th>\n",
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+ " <td>example_audio/chunks/oden_kypsis16k_chunk_7.wav</td>\n",
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+ " <td>enamus ajast nagu klikid neid allserva tekivad</td>\n",
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+ " <td>0.700862</td>\n",
623
+ " <td>7.0</td>\n",
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+ " <td>0.100123</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>3</th>\n",
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+ " <td>example_audio/chunks/oden_kypsis16k_chunk_8.wav</td>\n",
629
+ " <td>enamus ajast nagu klikid neid allserva tekivad...</td>\n",
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+ " <td>0.839978</td>\n",
631
+ " <td>8.0</td>\n",
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+ " <td>0.104997</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>4</th>\n",
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+ " <td>example_audio/chunks/oden_kypsis16k_chunk_9.wav</td>\n",
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+ " <td>enamus ajast nagu klikid neid allserva tekivad...</td>\n",
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+ " <td>1.016149</td>\n",
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+ " <td>9.0</td>\n",
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+ " <td>0.112905</td>\n",
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+ " </tr>\n",
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+ " </tbody>\n",
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+ "</table>\n",
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+ "</div>"
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+ ],
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+ "text/plain": [
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+ " file \\\n",
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+ "0 example_audio/chunks/oden_kypsis16k_chunk_5.wav \n",
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+ "1 example_audio/chunks/oden_kypsis16k_chunk_6.wav \n",
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+ "2 example_audio/chunks/oden_kypsis16k_chunk_7.wav \n",
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+ "3 example_audio/chunks/oden_kypsis16k_chunk_8.wav \n",
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+ "4 example_audio/chunks/oden_kypsis16k_chunk_9.wav \n",
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+ "\n",
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+ " hyp elapsed_time \\\n",
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+ "0 enamus ajast nagu klik 0.418611 \n",
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+ "1 enamus ajast nagu klikid neid all 0.481883 \n",
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+ "2 enamus ajast nagu klikid neid allserva tekivad 0.700862 \n",
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+ "3 enamus ajast nagu klikid neid allserva tekivad... 0.839978 \n",
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+ "4 enamus ajast nagu klikid neid allserva tekivad... 1.016149 \n",
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+ "\n",
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+ " audio_dur_sec trans_time_audio_dur_share \n",
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+ "0 5.0 0.083722 \n",
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+ "1 6.0 0.080314 \n",
664
+ "2 7.0 0.100123 \n",
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+ "3 8.0 0.104997 \n",
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+ "4 9.0 0.112905 "
667
+ ]
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+ },
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+ "execution_count": 39,
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+ "metadata": {},
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+ "output_type": "execute_result"
672
+ }
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+ ],
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+ "source": [
675
+ "df_chunk_times.columns=['file', 'hyp','elapsed_time', 'audio_dur_sec']\n",
676
+ "df_chunk_times['trans_time_audio_dur_share']=df_chunk_times.elapsed_time/df_chunk_times.audio_dur_sec\n",
677
+ "df_chunk_times=df_chunk_times.sort_values('audio_dur_sec')\n",
678
+ "df_chunk_times=df_chunk_times.reset_index(drop=True)\n",
679
+ "df_chunk_times.head()"
680
+ ]
681
+ },
682
+ {
683
+ "cell_type": "code",
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+ "execution_count": 40,
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+ "id": "1d8d9520-1bbd-43f5-ae7a-08643def9285",
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+ "metadata": {
687
+ "tags": []
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+ },
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/plain": [
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+ "<Axes: xlabel='elapsed_time', ylabel='audio_dur_sec'>"
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+ ]
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+ },
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+ "execution_count": 40,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ },
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+ {
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+ "data": {
702
+ "image/png": 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",
703
+ "text/plain": [
704
+ "<Figure size 640x480 with 1 Axes>"
705
+ ]
706
+ },
707
+ "metadata": {},
708
+ "output_type": "display_data"
709
+ }
710
+ ],
711
+ "source": [
712
+ "df_chunk_times.plot.scatter('elapsed_time', 'audio_dur_sec')"
713
+ ]
714
+ },
715
+ {
716
+ "cell_type": "code",
717
+ "execution_count": 41,
718
+ "id": "fcd06626-4e6e-4461-bf6b-7495bcc825b5",
719
+ "metadata": {
720
+ "tags": []
721
+ },
722
+ "outputs": [
723
+ {
724
+ "data": {
725
+ "text/plain": [
726
+ "Text(0.5, 0, 'audio duration')"
727
+ ]
728
+ },
729
+ "execution_count": 41,
730
+ "metadata": {},
731
+ "output_type": "execute_result"
732
+ },
733
+ {
734
+ "data": {
735
+ "image/png": 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",
736
+ "text/plain": [
737
+ "<Figure size 640x480 with 1 Axes>"
738
+ ]
739
+ },
740
+ "metadata": {},
741
+ "output_type": "display_data"
742
+ }
743
+ ],
744
+ "source": [
745
+ "df_chunk_times['trans_time_audio_dur_share'].plot()\n",
746
+ "plt.ylabel('transc time/audio duration ratio')\n",
747
+ "plt.xlabel('audio duration')"
748
+ ]
749
  }
750
  ],
751
  "metadata": {