Generate Subtitles from Video Free: A Practical Workflow

Extracting the Audio From Your Video Files

Before you can create subtitles, you need the audio. Most transcription tools only require the sound, not the video. The first step is to extract the audio track from your video files.

Working with one or two videos is straightforward. However, processing a large batch of social media clips one by one is inefficient. A bulk workflow is more practical in this scenario.

You will need a way to upload video files (like MP4 or MOV) and convert them to an audio-only format. A tool like Convert.FAST is designed for this. It allows you to drag and drop an entire folder of videos, process them simultaneously, and download the audio tracks in a single ZIP file.

Choosing an Audio Format: MP3 vs. WAV

When you extract the audio, you must choose a format. The two most common options are MP3 and WAV. The decision involves a trade-off between file size and quality.

• MP3 (Lossy) — This format uses lossy compression, which reduces file size by removing audio data that is hard for humans to hear. This can decrease file size by 75-95%. For transcription, this is usually sufficient. The smaller file size results in faster uploads and processing.
• WAV (Lossless) — A WAV file is an uncompressed, lossless copy of the original audio. It retains all data, which is useful for studio recording but unnecessary for transcription. The files are large, leading to longer upload times with no significant benefit for this use case.

The overall process can be visualized in three main stages, starting with audio extraction. The flow is simple: extract the audio from the video, convert that audio into text, and then format the text into a timed SRT file. If you need to further optimize file sizes after extraction, you can use Compress.FAST for audio compression.

A Note on Privacy

When you upload files to a web service, consider privacy. Check how the service handles your data.

This ensures your content is not stored indefinitely on a third-party server. If you want a more detailed explanation of this first step, we have a complete guide on how to extract audio from video. With your audio files ready, the next step is transcription.

Transcribing Your Audio with Free AI Tools

Once you have your audio files, you need to convert speech into text. There are two primary approaches: running software locally on your computer or using an online, cloud-based service. The choice involves a trade-off between privacy and convenience.

Local vs. Cloud Transcription

Running a transcription model locally means all processing happens on your machine. Tools like OpenAI's Whisper are suitable for this; your audio files are not sent over the internet. This is the preferred method for sensitive material. The trade-off is that you need a sufficiently powerful computer and some technical knowledge to set it up.

Cloud-based platforms offer convenience. You upload your audio file to a website, and their servers perform the transcription. This is fast and requires no local computing resources. The downside is that you are entrusting your data to a third party. Always review their privacy and data retention policies before uploading.

The best choice depends on your project. A developer creating an internal training video might prefer a local model. A YouTuber captioning a public video might find the speed of a cloud service more beneficial.

Either tool will produce a raw text file. This is a good starting point, but it is not a finished subtitle file. You can find more details in our guide on how to convert audio to text online.

Setting Realistic Expectations for Accuracy

Modern free AI tools can achieve over 90% accuracy with clear audio and a single speaker. However, real-world audio often presents challenges that can reduce performance.

• Background Noise — Sounds like air conditioning or background conversations can interfere with transcription.
• Accents — Strong regional accents or non-native speakers can be difficult for models to understand.
• Overlapping Speakers — The AI may struggle to distinguish between multiple people speaking at once.
• Specialized Language — Industry jargon, brand names, and acronyms are common sources of errors.

Manually transcribing a one-hour video could take a full day and cost several hundred dollars. An AI can produce a draft in minutes for free. This is useful, as a 2019 Verizon Media study found that over 80% of users watch videos with the sound off, and good subtitles can increase watch time by up to 15%.

Turning Your Transcript Into Timed Subtitles

The standard format for this is SRT (SubRip Text), though VTT (WebVTT) is also widely supported for web-based players.

An SRT file is a plain text file with a specific structure. Each subtitle entry includes a sequence number, a start and end time, and the text to display. This structure tells the video player when to show and hide each line of dialogue.

What an SRT File Looks Like

The format is clean and readable once you understand its components. Here is an example of two entries in a standard SRT file:

1
00:00:05,250 --> 00:00:07,800
This is the first line of dialogue.

2
00:00:08,100 --> 00:00:10,500
And this is the second line.

The timestamp format is hours:minutes:seconds,milliseconds. The millisecond precision allows for accurate synchronization with the audio.

The Process of Syncing and Timing

To convert your plain text to a polished SRT file, you will need a subtitle editor. Free, open-source tools like Subtitle Edit or Aegisub are effective options. They provide a visual interface that displays the video, audio waveform, and captions simultaneously, which simplifies the process.

The typical workflow is as follows:

This part of the process requires patience. A caption that appears too early or lingers too long can be distracting. The goal is to make the timing feel natural.

Considering Readability

Correct timing is important, but formatting also matters. A well-formatted subtitle file is easier to read. For instance, breaking a long sentence across two separate subtitle cues can improve pacing and comprehension.

This is where automation ends and human judgment begins. To see how this fits into the larger workflow, you can read more about the audio-to-SRT conversion process. With your timed SRT file ready, you are close to finishing.

Refining and Polishing Your Subtitle File

Automated transcription provides a first draft, not a finished product. Human review is necessary to achieve a professional result. The AI handles the initial transcription, but your judgment provides the final polish.

AI models are good at recognizing words but can miss context. They may misinterpret jargon, brand names, or homophones (e.g., "their" vs. "there"). For example, an AI once transcribed "Kubernetes" as "Kufubernetes" in a technical tutorial. This type of error can affect credibility. The manual review is your opportunity to catch these errors.

The Details of the Review Process

It is best to approach the review systematically. First, correct the text, then adjust the timing. The objective is a subtitle track that is accurate, synchronized, and easy to read.

Here is what to look for:

• Spelling and Grammar — Correct any typos or grammatical errors made by the AI.
• Punctuation and Flow — Use commas, periods, and line breaks to match the speaker's natural cadence. Proper punctuation can make a sentence flow better.
• Timestamp Sync — Adjust the start and end times for each line of text. The subtitle should appear when the speaker begins and disappear shortly after they finish.

Using a plain text editor for this is difficult. A dedicated subtitle editor is recommended. Most provide a side-by-side view of the video, audio waveform, and subtitles, which simplifies timestamp adjustments.

Including Non-Dialogue Cues for Accessibility

Good subtitles capture more than just spoken words. They convey the entire auditory experience, which is important for viewers who are deaf or hard of hearing. Including non-dialogue cues makes your content more accessible.

These are short, descriptive notes in brackets that explain important sounds. Consider including cues for sounds such as:

• Atmosphere — [upbeat music] can indicate the mood of a scene.
• Key Sound Effects — [phone rings] or [door closes] can be important to the narrative.
• Speaker IDs — When multiple people are speaking, [Sarah] I agree helps prevent confusion.

This final layer of polish elevates a decent subtitle file to a professional one. It creates a more inclusive viewing experience.

Sidecar vs. Burned-In Subtitles

You have a polished SRT file. Now you must decide how to deliver it with your video. The two main options are a sidecar file or burned-in subtitles. The best choice depends on where your video will be viewed.

When to Use Sidecar Files

A sidecar file is the separate .srt file you created. You upload it alongside your video on platforms like YouTube or Vimeo. This is the recommended approach for most long-form content because it is flexible.

• Viewer Control — Viewers can turn captions on or off.
• Accessibility — You can provide subtitle files in multiple languages.
• SEO — The text is indexable by search engines, which can help users find your video.

This is the professional, full-featured option.

When to Use Burned-In Subtitles

Burned-in subtitles (also called hardcoded or open captions) are permanently rendered onto the video frames. They cannot be turned off. This is the standard for platforms like Instagram, TikTok, or LinkedIn, where videos often autoplay without sound. Burned-in subtitles ensure your message is delivered even if the audio is muted.

The decision is a trade-off between control and compatibility. Sidecar files give the user and search engines more control. Burned-in subtitles guarantee the message is seen everywhere, but you lose flexibility and SEO benefits.

The demand for subtitled video is growing. The global market for AI subtitle generation is projected to increase significantly through 2032. Subtitled content can increase user engagement by up to 40%.

Your Subtitle Generation Questions Answered

Here are direct answers to common questions about generating subtitles from video.