> ## Documentation Index > Fetch the complete documentation index at: https://docs.videodb.io/llms.txt > Use this file to discover all available pages before exploring further. # AI Voiceovers > Add professional narration to silent footage > **Case: Automatically Creating Voiceover for Silent Footage of the Underwater World**

## Overview Voiceovers are the secret sauce that turns silent footage into captivating stories. They add depth, emotion, and excitement, elevating the viewing experience. Traditionally, this workflow required stitching together multiple tools: one for script writing (LLM), one for voice generation (TTS), and another for video editing. **VideoDB** simplifies this by bringing everything under one roof. In this tutorial, we will: 1. **Upload** a silent video. 2. **Analyze** the video to understand its visual content. 3. **Generate** a narration script using VideoDB's text generation. 4. **Generate** a professional AI voiceover using VideoDB's voice generation. 5. **Merge** them instantly into a final video. ## Setup ### Installing VideoDB ```python Python theme={null} !pip install videodb ``` ```javascript Node.js theme={null} npm install videodb ``` ### API Keys You only need your VideoDB API Key. Get your API key from [VideoDB Console](https://console.videodb.io). Free for first 50 uploads, no credit card required. ## Implementation ### Step 1: Connect to VideoDB Connect to VideoDB using your API key to establish a session. ```python Python theme={null} import videodb # Set your API key api_key = "your_api_key" # Connect to VideoDB conn = videodb.connect(api_key=api_key) coll = conn.get_collection() ``` ```javascript Node.js theme={null} import { connect } from 'videodb'; // Connect to VideoDB const conn = await connect({ apiKey: process.env.VIDEO_DB_API_KEY }); const coll = await conn.getCollection(); ``` ### Step 2: Upload Video We'll upload the silent underwater footage directly from YouTube. ```python Python theme={null} # Upload a video by URL video = coll.upload(url='https://youtu.be/RcRjY5kzia8') ``` ```javascript Node.js theme={null} // Upload a video by URL const video = await coll.uploadURL({ url: 'https://youtu.be/RcRjY5kzia8' }); ``` ### Step 3: Analyze Visuals We need to know what is happening in the video to write a script for it. We'll use `index_scenes()` to analyze the visual content. ```python Python theme={null} video_scenes_id = video.index_scenes() ``` ```javascript Node.js theme={null} const videoScenesId = await video.indexScenes(); ``` Let's view the description of first scene from the video ```python Python theme={null} video_scenes = video.get_scene_index(video_scenes_id) import json print(json.dumps(video_scenes[0], indent=2)) ``` ```javascript Node.js theme={null} const videoScenes = await video.getSceneIndex(videoScenesId); console.log(JSON.stringify(videoScenes[0], null, 2)); ``` **Output:** ```json theme={null} { "description": "The scene immerses the viewer in a vibrant, fluid expanse dominated by myriad blue and aqua forms. These countless, somewhat irregular shapes are densely packed, giving the impression of an immense, teeming mass in constant, gentle motion. Each form possesses a darker core that gradually lightens towards its edges, creating a translucent, almost glowing effect, as if illuminated from within. The varying shades, ranging from deep sapphire to brilliant turquoise, blend and shift across the frame, conjuring the image of a vast underwater environment. It evokes a colossal school of luminous marine creatures, perhaps fish or jellyfish, drifting together in a mesmerizing, organic dance, filling the visual field with their shimmering presence and dynamic, watery energy.", "end": 15.033, "metadata": {}, "scene_metadata": {}, "start": 0.0 } ``` ### Step 4: Generate Script Now, we use VideoDB's `generate_text` method to write a voiceover script based on the scene descriptions we just retrieved. ```python Python theme={null} # Construct a prompt with the scene context scene_context = "\n".join([f"- {scene['description']}" for scene in video_scenes]) prompt = f""" Here is a visual description of a video about the underwater world: {scene_context} Based on this, write a short, engaging voiceover script in the style of a nature documentary narrator (like David Attenborough). Keep it synced to the flow of the visuals described. Return ONLY the raw text of the narration, no stage directions or titles. """ # Generate the script using VideoDB script_response = coll.generate_text( prompt=prompt, model_name="pro") script_text = script_response["output"] print("--- Generated Script ---") print(script_text) ``` ```javascript Node.js theme={null} // Construct a prompt with the scene context const sceneContext = videoScenes.map(scene => `- ${scene.description}`).join('\n'); const prompt = ` Here is a visual description of a video about the underwater world: ${sceneContext} Based on this, write a short, engaging voiceover script in the style of a nature documentary narrator (like David Attenborough). Keep it synced to the flow of the visuals described. Return ONLY the raw text of the narration, no stage directions or titles. `; // Generate the script using VideoDB const scriptResponse = await coll.generateText( prompt, "pro" ); const scriptText = scriptResponse.output; console.log("--- Generated Script ---"); console.log(scriptText); ``` ### Step 5: Generate Voiceover Audio We can now turn that text into speech using `generate_voice`. This returns an Audio object directly, so we don't need to save or upload files manually. ```python Python theme={null} # Generate speech directly as a VideoDB Audio Asset audio = coll.generate_voice( text=script_text, voice_name="Default") print(f"Generated Audio Asset ID: {audio.id}") ``` ```javascript Node.js theme={null} // Generate speech directly as a VideoDB Audio Asset const audio = await coll.generateVoice( scriptText, "Default" ); console.log(`Generated Audio Asset ID: ${audio.id}`); ``` ### Step 6: Compose the Video We have the video and the generated voiceover. Now we merge them using the Timeline Editor. ```python Python theme={null} from videodb.editor import Timeline, Track, Clip, VideoAsset, AudioAsset # Create a timeline timeline = Timeline(conn) # 1. Create a Video Track video_track = Track() video_asset = VideoAsset(id=video.id) # Add the video clip video_clip = Clip(asset=video_asset, duration=float(video.length)) video_track.add_clip(0, video_clip) # 2. Create an Audio Track for the voiceover audio_track = Track() # Use the audio object we generated in Step 5 audio_asset = AudioAsset(id=audio.id) audio_clip = Clip(asset=audio_asset, duration=float(audio.length)) audio_track.add_clip(0, audio_clip) # Add tracks to timeline timeline.add_track(video_track) timeline.add_track(audio_track) ``` ```javascript Node.js theme={null} import { EditorTimeline, Track, Clip, EditorVideoAsset, EditorAudioAsset } from 'videodb'; // Create a timeline const timeline = new EditorTimeline(conn); // 1. Create a Video Track const videoTrack = new Track(); const videoAsset = new EditorVideoAsset({ id: video.id }); // Add the video clip const videoClip = new Clip({ asset: videoAsset, duration: parseFloat(video.length) }); videoTrack.addClip(0, videoClip); // 2. Create an Audio Track for the voiceover const audioTrack = new Track(); // Use the audio object we generated in Step 5 const audioAsset = new EditorAudioAsset({ id: audio.id }); const audioClip = new Clip({ asset: audioAsset, duration: parseFloat(audio.length) }); audioTrack.addClip(0, audioClip); // Add tracks to timeline timeline.addTrack(videoTrack); timeline.addTrack(audioTrack); ``` ### Step 7: Review and Share Generate the final stream URL and watch your AI-narrated video! ```python Python theme={null} from videodb import play_stream stream_url = timeline.generate_stream() play_stream(stream_url) ``` ```javascript Node.js theme={null} const streamUrl = await timeline.generateStream(); console.log(streamUrl); ``` **Output:**