Search Phrase = doubles
Automated Video Production Pipeline
This video guides you through setting up an automated video production pipeline, from selecting and testing brand voices using Eleven Labs to pairing them with digital avatars in HeyGen. By following the steps, you'll learn how to catalog and integrate voices, match them with visual characters, and generate preview videos for evaluation. Once you complete the video, you'll be able to efficiently create, test, and organize multiple spokesperson options for your brand's automated content generation. This process empowers you to streamline video production and build a scalable library of branded video assets.
Following are the key things you will be able to do after you watch this demo:
Identify suitable brand voices using generative AI tools.
Catalog and organize voice and avatar options for efficient selection.
Integrate third-party voices into video production platforms.
Pair voices with digital avatars to create compelling spokesperson combinations.
Generate and preview automated video content for evaluation.
Document and track production assets for streamlined workflow.
Select and finalize top spokesperson options for automated content generation.
Introduction to Automated Video Production Pipeline (00:00:00 – 00:00:59)
Josh kicks off the demo by outlining the goal: selecting brand-aligned voices and digital doubles (either your own clone or hired actors), organizing those assets, and laying out the end-to-end steps needed to spin up a fully automated video production pipeline.
Content Sequencing Concept and Cloning (00:00:59 – 00:02:20)
He explains the core idea of building a repeatable sequence of content—cloning a finished production over and over—so you can continually generate new videos by plugging different scripts into the same automated workflow.
Defining Digital doubles and Voice Types (00:02:20 – 00:03:11)
Josh clarifies terminology (digital twin vs. digital double), walks through the two main “buckets” of voice assets (personality-based clones vs. spokesperson avatars), and discusses how to mix and match them depending on your brand needs.
Selecting Platforms for Generative AI and Deployment (00:03:11 – 00:04:00)
He emphasizes the importance of vetting your generative-AI tools—voice engines and video avatars—and making sure they’re compatible with your target platforms before committing to any given solution.
Brand-Focused Workflow and SRT Utilization (00:04:00 – 00:05:25)
Josh decides to focus on one streamlined method for this demo, using a single SRT transcript file as the “source of truth” for automation—underscoring that a clean, well-formatted SRT is absolute gold when you’re architecting an automated pipeline.
Importing SRT and Leveraging Automation (00:05:25 – 00:07:40)
He shows how to import the SRT into the voice-generation platform, highlighting how the time-coded script drives every subsequent step—from audio rendering to scene assembly.
Setting Up Voice Design in ElevenLabs (00:07:40 – 00:11:49)
A step-by-step walkthrough of testing voice presets, tweaking text lengths, integrating third-party voices, and crafting voice-design prompts to nail down the exact tone and style you want.
Managing Credits and Reviewing Generated Audio (00:11:49 – 00:15:46)
Josh demonstrates how to monitor and conserve your generation credits, preview the rendered audio, swap out placeholder text, and ensure you’re only spending resources on polished clips.
Applying Voiceover and Text Overlays to Video (00:15:46 – 00:19:08)
He attaches the finalized voice track to the video timeline, adds and styles text overlays (centering, contrast adjustments), and assembles the basic video composition ready for export.
Enhancing Prompts with AI Tools for Voice Design (00:19:08 – 00:22:04)
Introduces additional AI utilities for brainstorming and refining your voice-design prompts—showing how to iterate until you get a sample that truly matches your brand voice.
API Key Handling and Asset Export Configuration (00:22:04 – 00:27:28)
A practical guide on securely copying your ElevenLabs API key, configuring export settings (e.g., 4K output), and organizing all generated files into branded folders for easy access.
Frame Rate Considerations and Quality Checks (00:27:28 – 00:31:42)
Notes the default 25 fps setting, explains how frame rate impacts perceived motion, and walks through checking your export quality to avoid any unexpected artifacts.
Avatar Adjustments, Project Naming, and Fallbacks (00:31:42 – 01:05:16)
Josh covers fine-tuning avatar scale and positioning, updating project names for consistency, and setting up fallback workflows if you need to swap voices or visuals mid-pipeline.
Avatar Replacement and Cataloging (00:31:42 – 00:34:06)
Pair your chosen voice with visuals by replacing the default avatar, browsing through the 21 “looks” in each category, using the snipping tool to capture promising thumbnails, and logging each candidate’s name and category in your tracking spreadsheet.
Avatar Testing and Video Formatting (00:34:07 – 00:36:24)
Brainstorm voice–visual combinations (e.g. “August”), select a portrait-mode avatar, preview the static image, upload any custom avatars into the pipeline, drag your source video beneath the avatar layer, and confirm the composition and framing.
Voice-Avatar Sync and Quality Comparison (00:36:24 – 00:37:39)
Generate audio samples to compare HeyGen vs. ElevenLabs quality, force-refresh the clip to confirm it’s using the intended voice (e.g. Ryan Kirk), and watch for the spinning indicator to verify successful render.
Preview Generation and File Labeling (00:38:10 – 00:39:11)
Render a 4K preview of the voice-avatar pairing, then label the export asset with your convention (e.g. 001_RyanKirk_CharlieAvatar) so each test remains organized and easily identifiable.
Pipeline Duplication for Variant Testing (00:39:11 – 00:41:15)
Duplicate the entire sequence to create “Test 002,” swap in a new avatar (such as Colton), explore lifestyle/UGC categories, and note how background removal and frame size affect the final look.
Background Removal and Frame Adjustments (00:41:15 – 00:42:32)
Apply the background-remover tool to avatars with built-in backgrounds, observe any cut-offs (like arms being cropped), tweak the canvas framing, and decide between static vs. transparent backgrounds based on brand needs.
Third-Party Voice Integration Workflow (00:42:32 – 00:44:03)
In the “My Voices” tab, toggle on integrated voices (e.g. Charlie), heart your favorites so they surface first, preview each sample, and ensure the API integration is active before proceeding.
Voice Audition Labeling and Mood Board Documentation (00:44:03 – 00:47:09)
Name each audition (e.g. 002_CharlieAvatar), update your mood board with snipped thumbnails, record which browser tab or category each came from, and keep this documentation up to date for reproducibility.
Frame Rate and Credit Management (00:47:09 – 00:48:06)
Note the default 25 fps setting—mismatches can cause audio sync issues—toggle off “Avatar 4” if you’re on an unlimited plan, and monitor your generation credits to avoid unexpected limits.
Styling and Folder Organization (00:48:06 – 00:49:29)
Adjust text overlay colors to maintain contrast (match your brand palette), create new folders for each batch, and standardize your output directory structure so you know exactly where each rendered clip lives.
Option Preview and Cataloging Workflow (00:49:30 – 00:55:51)
Refresh thumbnails, scroll through voice-avatar combos, assign option numbers, screenshot grids of candidates, and log each pairing’s status (“Yes,” “Maybe,” “No”) in your spreadsheet.
Iteration Process and Consistency Notes (00:55:51 – 00:57:23)
Always regenerate every variation (never reuse stale renders), note any limitations (e.g. animated text can cover on-screen elements), and keep your naming and documentation consistent so the pipeline remains bullet-proof.
Ranking Options and Visual Separators (00:57:24 – 01:02:40)
Introduce visual separators in your catalog (e.g. blank rows), rank the top voice-avatar combos, screenshot your “definite yes” list, and preserve those as templates for future batches.
Additional Voice Integration: Amelia (01:02:40 – 01:04:33)
Search for “Amelia” in your voice library, verify whether it’s built-in or needs third-party integration, add it to favorites, preview the sample, and record its ID for consistent reuse.
Final Voice Candidate Integration (01:04:33 – 01:05:16)
Confirm Amelia’s render, then search for any last candidates (e.g. “Analore”), heart and test them, catalog the results, and ensure each new voice is fully integrated into the pipeline.
Final Pipeline Recap and Scale Duplication (01:07:40 – 01:08:34)
Recap how you’ve selected your final set of voices and avatars, finalize your naming conventions, and highlight that you can now duplicate this entire automated workflow to churn out an endless library of on-brand social-media videos.
Keywords: automation,content,creation,production,studio,digital,doubles,video,avatar,text,script,cloud-based,tools,slide,decks,PowerPoint,Canva,training,programs,staff,development,retention,coding,Academy,method,four
Method Four of the Ultimate Content Creation Workflow enables creators to automate their entire video production process by leveraging cloud-based tools and digital technology. By mastering this method, content creators can clone their voice, generate video avatars, and produce high-quality training videos and presentations with minimal time and effort. The workflow allows you to transform a simple text script into a fully automated video production, complete with synchronized audio, visuals, and slide decks. Ultimately, this approach empowers busy professionals to scale their content creation without being constrained by traditional time-consuming production methods.
Method Four of the Ultimate Content Creation Workflow enables creators to automate their entire video production process by leveraging cloud-based tools and digital technology. By mastering this method, content creators can clone their voice, generate video avatars, and produce high-quality training videos and presentations with minimal time and effort. The workflow allows you to transform a simple text script into a fully automated video production, complete with synchronized audio, visuals, and slide decks. Ultimately, this approach empowers busy professionals to scale their content creation without being constrained by traditional time-consuming production methods.
Here are the key things you will be able to do after you watch this demo:
Clone your voice for digital content creation
Generate automated video avatars
Transform text scripts into complete video presentations
Automate slide deck production in PowerPoint and Canva
Scale content creation with minimal time investment
Develop training materials efficiently
Leverage cloud-based production tools
Create digital doubles of yourself
Streamline video production workflows
Produce high-quality educational content without extensive technical skills
Ultimate Content Creation Workflow Overview 0:08
Josh Lomelino introduces method four, which automates the entire content creation process.
This method combines the first three methods but focuses on automation, making it more efficient.
Josh emphasizes the importance of mastering the first three methods before attempting method four.
The method allows for the creation of high-quality content with minimal time, effort, and budget.
Method Four's Impact on Production 1:09
Josh describes the transformative power of method four, which revolutionized his production process.
A potential customer expressed interest in using the method for staff development and retention.
Josh explains how he creates digital doubles of himself to automate the production process.
The method enables large-scale production without the time constraints typically associated with video creation.
Addressing Time Constraints in Content Creation 1:49
Josh shares experiences of customers who face time constraints in creating training programs and classes.
He highlights the challenges of maintaining a busy schedule while keeping up with production demands.
Method four allows for the cloning of voices and creation of audio tracks to generate video avatars.
The method significantly reduces the time required to produce multiple videos.
Automation Capabilities of Method Four 2:29
Josh explains that everything in the final video is fully automated, starting from a text script.
The process involves copying and pasting the script into cloud-based production tools.
High-end computers are not necessary as most of the heavy lifting is done in the cloud.
The method also automates the creation of slide decks in tools like PowerPoint or Canva.
Step-by-Step Process Walkthrough 2:48
Josh mentions that he will walk through each part of the process in the following sections.
The detailed steps will provide a comprehensive understanding of method four.
The process aims to make content creation more efficient and less time-consuming.
Josh emphasizes the importance of understanding each step to effectively implement the method.
Keywords: Digital, doubles, AI, tools, lighting, image, quality, training, model, green
In this tutorial, Josh guides viewers through creating high-quality digital doubles using AI technology. By following his detailed workflow, users will learn how to record themselves with optimal lighting, camera angles, and techniques to capture natural movements. The process involves creating multiple avatar variations with a consistent naming system, allowing for seamless video production and editing. After completing the tutorial, viewers will be able to generate professional, versatile digital avatars that can be used across different video projects with ease and consistency.
In this tutorial, Josh guides viewers through creating high-quality digital doubles using AI technology. By following his detailed workflow, users will learn how to record themselves with optimal lighting, camera angles, and techniques to capture natural movements. The process involves creating multiple avatar variations with a consistent naming system, allowing for seamless video production and editing. After completing the tutorial, viewers will be able to generate professional, versatile digital avatars that can be used across different video projects with ease and consistency.
Following are the key things you will be able to do after you watch this demo:
Create multiple avatar variations with a consistent naming system
Record high-quality source footage for AI digital double training
Select optimal recording environments (green screen or natural settings)
Capture multiple camera angles for flexible video production
Apply three-point lighting techniques for professional video quality
Use camera settings to record in 4K resolution
Develop a systematic approach to avatar creation and management
Experiment with different avatar styles and gestures
Optimize video recording for AI digital double learning
Implement a multi-camera editing workflow for seamless avatar transitions
Building Digital doubles from Scratch 0:08
Josh Lomelino explains the importance of following earlier steps, especially around lighting and image quality, to avoid costly post-production fixes.
He emphasizes the need for a two-minute video of oneself speaking directly to the camera, suggesting the use of a wireless mouse for discreet recording.
Josh prefers recording against a green screen for flexibility in background changes, but acknowledges the natural setting option.
He recommends experimenting with different avatars, using a consistent numbering system for organization, and provides examples of naming conventions for avatar variations.
Creating and Managing Avatars 3:19
Josh discusses the importance of capturing as many versions as possible for each outfit in one session to ensure consistency in hair, lighting, and clothing.
He explains his approach to recording multiple shots or angles simultaneously using different camera angles and a multi-cam edit in video editing software.
The three essential angles he always records are a close-up, a medium shot, and a three-quarter side view.
Josh mentions the challenges some AI tools pose with the three-quarter view but recommends capturing it for added realism and variety.
Recording and Equipment Considerations 4:43
Josh advises using a Logitech 4K webcam for better image quality, though a 1080p camera can also yield decent results.
He shares his experience with different recording devices, including a phone's rear-facing camera in 4K, a webcam, and a DSLR, and emphasizes the need for experimentation.
Josh recommends using the built-in Windows or Mac camera app for recording at the highest resolution possible, with instructions on adjusting settings to force 4K recording.
He advises recording a clip without the green screen, looking straight into the camera, and speaking casually to ensure the digital double learns natural behavior.
Batch Creating Avatars 6:07
Josh introduces a workflow in his video editing software for batch creating avatars, which speeds up the process.
He mentions the importance of recording a clip that is at least two minutes long to avoid issues with awkward movements being mimicked by the avatar.
Josh explains his setup for recording, including using an adjustable camera arm mounted to his desk for flexibility.
He concludes the demo by stating that he will cover more in the next video, indicating the end of the current session.
Keywords: Green screen, virtual avatar, training video, RGB, Ultra Key
In this tutorial, Josh demonstrates how to create a versatile virtual avatar using a green screen background. By following his step-by-step process, viewers will learn to record a training video, use video editing software to remove the background, and export a high-quality 4K file for avatar creation. The technique allows users to generate a digital double that can be placed on any background, enabling them to create numerous training videos, presentations, and lectures without being physically present. Ultimately, viewers will gain the skills to produce an AI avatar that can work continuously, freeing up their personal time while maintaining professional content production.
In this tutorial, Josh demonstrates how to create a versatile virtual avatar using a green screen background. By following his step-by-step process, viewers will learn to record a training video, use video editing software to remove the background, and export a high-quality 4K file for avatar creation. The technique allows users to generate a digital double that can be placed on any background, enabling them to create numerous training videos, presentations, and lectures without being physically present. Ultimately, viewers will gain the skills to produce an AI avatar that can work continuously, freeing up their personal time while maintaining professional content production.
Following are the key things you will be able to do after you watch this demo:
Shoot a training video using a green screen background
Apply the ultra key filter in video editing software
Create a 100% green color matte
Remove background elements from video footage
Export high-quality 4K video files
Generate a virtual avatar using AI software
Render digital doubles for multiple presentations
Layer virtual avatars over different backgrounds
Integrate avatar presentations with PowerPoint and Canva slides
Produce training content without physical studio time
Creating a Virtual Avatar with a Green Screen Background 0:08
Josh Lomelino explains the importance of using a green screen background for creating virtual avatars, emphasizing versatility and ease of use.
He describes the general principle of achieving a 100% green background in the RGB model, noting the difficulty of achieving perfect green.
Josh introduces simple steps to help with the process, including shooting a two-minute training video on a green screen and using 100% green shapes in video editing software.
He demonstrates the use of the ultra key filter in video editing software to eliminate the background and adjust settings like feathering, key color, and matte cleanup.
Setting Up the Green Screen Workflow 5:18
Josh explains the creation of a 100% green color matte in video editing software, specifying the width and height to be 4k.
He describes layering the green clip underneath the video track and extending it to the same length as the training clip.
Josh mentions the importance of placing additional green color mats to fix any spillover areas and avoid relying solely on the ultra key effect.
He outlines the process of setting in and out points, exporting the clip as an MP4 file, and using Adobe Media Encoder for batch rendering.
Exporting and Adjusting Settings 8:12
Josh details the export settings, including using the h264 codec for high quality and specifying the file type as MP4.
He emphasizes the importance of evenly lighting the green screen for a better key and mentions common issues like wrinkles and folds.
Josh shows how to create a new avatar in Hey Gen or other virtual avatar software, validating the model by reading a code aloud.
He explains the process of uploading source material, validating the camera angle, and retaining 4k footage for higher resolution renders.
Using the Virtual Avatar in Various Productions 11:27
Josh discusses the flexibility of using the virtual avatar in presentations, lectures, and demos, including mixing with PowerPoint slides and Canvas slides.
He highlights the ability to create unlimited digital doubles and the importance of not checking the AI remove background option.
Josh explains the use of Camtasia's Remove Color effect to key out the green color in the background and the importance of using high-quality settings.
He advises against using proxy footage for making decisions about green screen settings and emphasizes the need for maximum quality settings in video editing software.
Final Steps and Infinite Possibilities 14:54
Josh concludes by mentioning the infinite possibilities of the workflow, including creating presentations directly inside Hey Gen.
He discusses integrating with Canva for timed slide changes and animations, and the option to check the background removal button for a transparent background.
Josh reiterates the importance of using the method shown in the video to achieve 4k production quality, even if it requires a more expensive plan.
He wraps up the demo, encouraging viewers to explore the various applications and approaches for their virtual avatars.
Keywords: batch, avatar, digital-double, production, lighting, setup, color, correction, video, editing, project, HeyGen, encoder
In this tutorial, Josh Lomelino demonstrates a comprehensive workflow for efficiently batch producing multiple virtual avatars with consistent lighting and color quality. Viewers will learn how to set up precise video editing project settings, create a master sequence with multiple camera angles, and use Adobe Media Encoder to render individual clips for avatar training. The technique allows content creators to scale their avatar production, quickly export multiple versions of their digital doubles, and maintain a well-organized project structure that enables future edits and refinements. By following this method, users can streamline their avatar creation process, saving significant time and producing high-quality, professional virtual representations.
In this tutorial, Josh Lomelino demonstrates a comprehensive workflow for efficiently batch producing multiple virtual avatars with consistent lighting and color quality. Viewers will learn how to set up precise video editing project settings, create a master sequence with multiple camera angles, and use Adobe Media Encoder to render individual clips for avatar training. The technique allows content creators to scale their avatar production, quickly export multiple versions of their digital doubles, and maintain a well-organized project structure that enables future edits and refinements. By following this method, users can streamline their avatar creation process, saving significant time and producing high-quality, professional virtual representations.
Following are the key things you will be able to do after you watch this demo:
Configure video editing project settings to match camera specifications
Create a systematic numbering and organization system for avatar sequences
Set up multiple camera angles within a single project
Use Adobe Media Encoder to batch render avatar clips
Export individual video files for virtual avatar training
Implement color correction and LUT modifications across multiple clips
Organize project files for efficient content production
Develop a scalable workflow for mass avatar creation
Troubleshoot and remove performance anomalies in avatar recordings
Back up and preserve digital asset production files
Setting Up Lighting and Color Values 0:08
Josh Lomelino explains the importance of setting up lighting and color values once to achieve consistent results over time.
He emphasizes the need to test lighting and color values before batch producing a group of avatars.
Josh mentions the flexibility to make further adjustments later using L, U, T color modifications or color correction tools.
The workflow allows for the efficient production of 10 to 50 avatars, ensuring visual polish from the start.
Consistency in Project Settings 1:42
Josh highlights the necessity of matching video editing project settings to the specifications of the recording camera.
He provides an example of setting up a project for a Logitech 4k camera and ensuring consistency in frame size and frame rate.
Josh advises checking file properties to extract frame size and frame rate if unsure.
Consistency in project settings is crucial for mass producing different clips.
Creating a Master Sequence 2:59
Josh sets up a master sequence to serve as a template for duplicating sequences as needed.
He uses a clear numbering system for sequences, labeling each avatar with a specific outfit and camera angle.
Examples include Avatar 001, DIRECT address, no hands, and Avatar 0013, quarter view.
Josh organizes sequences in a dedicated folder called a bin for project organization.
Batch Rendering with Adobe Media Encoder 4:56
Josh explains the process of adding clips to a Batch Render Queue using Adobe Media Encoder.
He selects in and out points for each camera angle, creating dedicated files for each angle.
Josh configures the encoder to render only the specified in and out range on the timeline.
Each camera angle should be exported as an individual MP4 file, specifying the folder location and file name.
Finalizing and Organizing Project Files 6:40
Josh emphasizes the importance of organizing project files, including original source files, rendered clips, and project files.
He advises saving the video editing project frequently as a fail-safe for future edits.
Josh highlights the need to review source footage for any performance anomalies and correct them.
The workflow allows for the removal of outdated avatars and recreation without problematic movements.
Backing Up and Scaling Content Production 8:25
Josh frequently backs up his entire project folder by compressing it into a zip file for disaster recovery.
He mentions the time investment upfront to create polished assets and resolve hiccups.
Josh advises starting with manual methods and gradually scaling to more advanced techniques.
The well-organized project structure saves time, enables content production scaling, and supports high-performance results.
Keywords: Automated, performance, text, video, Otter, AI, voice, clone, Eleven Labs, HeyGen, audio, multilingual
In this video, Josh demonstrates how to create fully automated video performances directly from text using tools like Otter AI, 11 Labs, and HeyGen. Viewers will learn how to generate high-quality voice clones, prototype video scripts, and produce professional-looking content with minimal effort by leveraging AI-powered voice and video generation technologies. The workflow allows content creators to transform written or spoken text into polished video presentations quickly and efficiently. By following Josh's method, users can generate multiple video iterations, edit audio precisely, and create digital avatars that replicate their voice and performance with remarkable accuracy.
In this video, Josh demonstrates how to create fully automated video performances directly from text using tools like Otter AI, 11 Labs, and HeyGen. Viewers will learn how to generate high-quality voice clones, prototype video scripts, and produce professional-looking content with minimal effort by leveraging AI-powered voice and video generation technologies. The workflow allows content creators to transform written or spoken text into polished video presentations quickly and efficiently. By following Josh's method, users can generate multiple video iterations, edit audio precisely, and create digital avatars that replicate their voice and performance with remarkable accuracy.
Following are the key things you will be able to do after you watch this demo:
Generate video scripts from transcribed audio using AI tools
Create high-quality voice clones with consistent audio recordings
Prototype video content using free and paid AI platforms
Optimize voice training for digital avatars
Manage content production across multiple AI environments
Edit audio tracks with minimal credit consumption
Develop a systematic workflow for automated video creation
Replicate personal performance using digital voice technology
Transform text-based content into professional video presentations
Implement cost-effective strategies for video and audio generation
Creating a Fully Automated Performance from Text 0:08
Josh Lomelino explains the process of creating a fully automated performance directly from text, including generating audio prompts using Otter AI.
He describes how he brainstorms ideas while walking and exports the subtitle transcript file, SRT, to process it with AI tools like Claude or ChatGPT.
Josh mentions breaking up long scripts into manageable blocks of 1800 characters and generating a year's worth of content for various platforms.
He emphasizes the use of text, whether written manually or spoken and transcribed, to craft a video script using two primary methods.
Generating High-Quality Voice Clones 1:51
Josh discusses creating a high-quality voice clone using 11 Labs, initially finding the results artificial but later perfecting the settings.
He highlights the importance of using a consistent audio clip for training the voice digital double, ideally around three hours of spoken audio.
Josh explains the challenges of recording consistently for three hours and how he stitches together previous demo recordings to create a large audio clip.
He stresses the need for meticulous tracking of audio settings to ensure uniformity and avoid sudden changes in volume or tonal quality.
Optimizing Audio Recording for Consistency 3:36
Josh shares his experience of recording multiple live sessions with an audience, which infused the audio with personality and energy.
He explains the importance of having consistently dialed-in audio for generating a high-quality performance, as the AI listens to everything in the audio track.
Josh mentions the time and cost involved in using 11 Labs, which can take up to six to eight hours to analyze a voice and build a model.
He advises against using cheaper models, such as the multilingual version one model or turbo 2.5, and recommends upgrading to the multilingual version two model for better results.
Using Hey Gen for Cost-Effective Prototyping 5:35
Josh introduces Hey Gen as an alternative for creating generative content when 11 Labs burns through credits too quickly.
He explains how he trains Hey Gen on his voice by uploading a 10 to 15-minute audio clip and generates unlimited videos for free, depending on the subscription plan.
Josh describes the process of creating prototypes, making real-time adjustments to the script, and rendering multiple takes.
He mentions using his phone in split screen mode while walking to make adjustments on the fly and then copying and pasting the revised script into Hey Gen.
Switching Between Hey Gen and 11 Labs 7:44
Josh explains how he can switch the voice in Hey Gen to the high-quality production voice in 11 Labs with a click of a button.
He highlights the downside of using Hey Gen, which is the risk of losing all credits if there are issues with the audio track in the final video.
Josh prefers using the Studio tool in 11 Labs for targeted editing, which allows regenerating just portions of the audio without redoing the entire clip.
He mentions the benefit of being able to download the WAV file and MP3 file from the Studio tool in 11 Labs as a fail-safe.
Organizing Video Production Phases 9:21
Josh describes his workflow of treating production as two phases: the cheap, free voice phase and the final phase.
He explains the process of pasting the text directly into the Hey Gen editor, listening to the prototype, and resolving issues before creating a new file in Hey Gen.
Josh organizes his videos into two folders: a prototype folder and a final folder, for easy organization of his methods.
He mentions using the multilingual version two model for cost-effective throwaway tests and training his voice with Hey Gen for free prototyping.
Leveraging Digital doubles for High-Quality Videos 10:34
Josh shares how he uses his digital doubles to replicate a performance of his voice and generate a corresponding video composite.
He explains how he creates a script using Otter AI during a walk, copies and pastes it into his automated workflow, and produces a high-end video with minimal effort.
Josh highlights the benefits of this workflow, which allows him to deliver excellence without skipping a beat, even when small inconsistencies would have derailed the process before.
He concludes by mentioning the next steps in the following videos, which will cover adding automated visual elements on screen behind the virtual avatar.
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