notebooks/transcript.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from pathlib import Path\n",
    "sys.path.append(\"../\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipywidgets as wdgt\n",
    "from pathlib import Path\n",
    "\n",
    "# Set up transcript file selection\n",
    "transcript_dir = Path('../data/transcripts')\n",
    "transcript_files = {f.stem: str(f) for f in transcript_dir.glob('*.json')}\n",
    "\n",
    "# Create and display dropdown widget\n",
    "transcript_select = wdgt.Dropdown(\n",
    "    options=transcript_files,\n",
    "    description='Select Transcript:',\n",
    "    layout=wdgt.Layout(width='75%')\n",
    ")\n",
    "\n",
    "# Initialize and update transcript path\n",
    "transcript_path = Path(transcript_files[next(iter(transcript_files))])\n",
    "\n",
    "def update_transcript_file(change) -> None:\n",
    "    global transcript_path\n",
    "    transcript_path = Path(change.new)\n",
    "    print(f\"Selected transcript: {transcript_path}\")\n",
    "\n",
    "transcript_select.observe(update_transcript_file, names='value')\n",
    "display(transcript_select)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "from collections import defaultdict\n",
    "from typing import Dict, List, Tuple\n",
    "\n",
    "# Load transcript data\n",
    "with open(transcript_path) as f:\n",
    "    transcript_data = json.load(f)\n",
    "\n",
    "async def analyze_transcript(transcript_path: Path) -> Dict:\n",
    "    \"\"\"\n",
    "    Analyze transcript content including speaker stats and timing information.\n",
    "    \n",
    "    Args:\n",
    "        transcript_path: Path to the transcript JSON file\n",
    "        \n",
    "    Returns:\n",
    "        Dict containing analysis results\n",
    "    \"\"\"\n",
    "\n",
    "    \n",
    "    # Initialize analysis containers\n",
    "    speaker_stats = defaultdict(lambda: {\n",
    "        \"total_time\": 0.0,\n",
    "        \"word_count\": 0,\n",
    "        \"segments\": 0\n",
    "    })\n",
    "    \n",
    "    total_duration = 0\n",
    "    \n",
    "    # Analyze segments from the segments list in the JSON structure\n",
    "    for segment in transcript_data[\"segments\"]:\n",
    "        speaker = segment[\"speaker\"] \n",
    "        duration = segment[\"end\"] - segment[\"start\"]\n",
    "        words = len(segment[\"words\"])\n",
    "        \n",
    "        # Update speaker statistics\n",
    "        speaker_stats[speaker][\"total_time\"] += duration\n",
    "        speaker_stats[speaker][\"word_count\"] += words\n",
    "        speaker_stats[speaker][\"segments\"] += 1\n",
    "        \n",
    "        total_duration = max(total_duration, segment[\"end\"])\n",
    "    \n",
    "    # Calculate summary statistics\n",
    "    analysis = {\n",
    "        \"total_duration\": total_duration,\n",
    "        \"total_speakers\": len(speaker_stats),\n",
    "        \"speaker_stats\": dict(speaker_stats)\n",
    "    }\n",
    "    \n",
    "    # Print summary\n",
    "    print(f\"\\nTranscript Analysis Summary:\")\n",
    "    print(f\"Total Duration: {total_duration:.2f} seconds\")\n",
    "    print(f\"Number of Speakers: {len(speaker_stats)}\")\n",
    "    print(\"\\nSpeaker Statistics:\")\n",
    "    \n",
    "    for speaker, stats in speaker_stats.items():\n",
    "        print(f\"\\n{speaker}:\")\n",
    "        print(f\"  Speaking Time: {stats['total_time']:.2f} seconds\")\n",
    "        print(f\"  Word Count: {stats['word_count']}\")\n",
    "        print(f\"  Number of Segments: {stats['segments']}\")\n",
    "        if stats['total_time'] > 0:\n",
    "            print(f\"  Words per Second: {stats['word_count']/stats['total_time']:.2f}\")\n",
    "            \n",
    "    return analysis\n",
    "\n",
    "# Run analysis on selected transcript\n",
    "analysis_results = await analyze_transcript(transcript_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_timestamp(seconds: float) -> str:\n",
    "    \"\"\"Convert seconds to HH:MM:SS format\"\"\"\n",
    "    hours = int(seconds // 3600)\n",
    "    minutes = int((seconds % 3600) // 60) \n",
    "    secs = int(seconds % 60)\n",
    "    return f\"{hours:02d}:{minutes:02d}:{secs:02d}\"\n",
    "\n",
    "from ipywidgets import HTML, VBox, Layout\n",
    "from textwrap import fill\n",
    "\n",
    "# Create formatted HTML output\n",
    "html_output = [\"<h3>Meeting Script - Combined by Speaker</h3>\"]\n",
    "html_output.append(\"<hr>\")\n",
    "\n",
    "current_speaker = None\n",
    "current_text = []\n",
    "current_start = None\n",
    "\n",
    "for segment in transcript_data[\"segments\"]:\n",
    "    if current_speaker != segment[\"speaker\"]:\n",
    "        # Output previous speaker's text\n",
    "        if current_speaker:\n",
    "            timestamp = format_timestamp(current_start)\n",
    "            wrapped_text = fill(' '.join(current_text), width=80)\n",
    "            html_output.append(f\"<p><b>[{timestamp}] {current_speaker}:</b><br>\")\n",
    "            html_output.append(f\"{wrapped_text}</p>\")\n",
    "            html_output.append(\"<hr>\")\n",
    "            \n",
    "        # Start new speaker\n",
    "        current_speaker = segment[\"speaker\"]\n",
    "        current_text = [segment[\"text\"].strip()]\n",
    "        current_start = segment[\"start\"]\n",
    "    else:\n",
    "        # Continue current speaker\n",
    "        current_text.append(segment[\"text\"].strip())\n",
    "\n",
    "# Output final speaker\n",
    "if current_speaker:\n",
    "    timestamp = format_timestamp(current_start)\n",
    "    wrapped_text = fill(' '.join(current_text), width=80)\n",
    "    html_output.append(f\"<p><b>[{timestamp}] {current_speaker}:</b><br>\")\n",
    "    html_output.append(f\"{wrapped_text}</p>\")\n",
    "    html_output.append(\"<hr>\")\n",
    "\n",
    "# Display formatted output\n",
    "display(HTML(\n",
    "    value=''.join(html_output),\n",
    "    layout=Layout(width='100%', border='1px solid gray', padding='10px')\n",
    "))\n"
   ]
  }
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