Subtitles: How to transcribe audio in the browser and get SRT
The Subtitles tool recognizes speech from uploaded audio directly in the browser and generates a text file with timestamps in SRT format. Audio is not sent to external servers: transcription is performed locally, which is important for confidential recordings. The tool does not create video, does not generate speech, and does not edit images — its narrow task is to turn sound into structured subtitles. In this article we will consider practical scenarios, show how to prepare audio and verify the result. All examples are fictional and provided to demonstrate the tool's capabilities.
Open tool: Subtitle generator ↗How the tool works and what is input
The interface is a web form with text fields. You upload an audio file, select the recognition language and click "Generate". Processing happens in the browser: sound is not sent to remote servers, it is transcribed locally. The result appears in a separate panel as text with timestamps. It can be copied or downloaded in TXT or SRT format.
Important to understand limitations: the tool does not perform batch processing, does not save history, does not integrate with video editors and does not support export to DOCX or PDF. Maximum length of a single request — 8000 characters for the main field and 1000 for additional details. Audio is limited to 20 MB and 5 minutes. If the recording is longer or heavier, it must be pre-cut. Recognition quality depends on speech clarity, noise level and presence of strong accent. The model may make mistakes in proper names, terms and numbers.
To get subtitles you do not need to write complex instructions — just specify the language and, if necessary, add context. For example, if the recording has many technical terms, you can list them in the additional field to increase accuracy. The tool does not require registration and has no premium plan. All features are available immediately.
Prompt: "Transcribe audio, language Russian. The recording mentions terms: API, Kubernetes, CI/CD. Keep timestamps."
Scenario 1: subtitles for a training webinar
Imagine you recorded a webinar on the topic "Introduction to Machine Learning" lasting 4 minutes. The recording has a lecturer with clear diction, but English terms occur: overfitting, gradient descent, validation set. Your task is to get an SRT file for subsequent upload to a platform. You upload the audio, select Russian and in the additional field list the terms that need to be recognized correctly.
After generation you get a file with timestamps. Check that the terms are written correctly and that the time intervals do not overlap. If the lecturer paused, the markers may shift — this is normal, but make sure the beginning and end of replicas match the audio. Pay attention to numbers: "0,85" may be recognized as "zero eighty five" — correct manually if needed.
The ready-made SRT can be loaded into a video editor or onto a platform for creating subtitles. The tool does not publish subtitles automatically and does not send them by email — you control the further steps. If the recording contains background music, accuracy may decrease; in such case try to pre-clean the audio.
Prompt: "Create subtitles for this audio. Language: Russian. Terms: overfitting, gradient descent, validation set. Format: SRT."
Scenario 2: interview with a guest in a podcast
You recorded a 5-minute interview with a cybersecurity expert. Two people participate in the conversation, sometimes they interrupt each other. The tool does not separate speakers by voice, so in the subtitles there will be continuous text. Your goal is to get a readable SRT for publishing in social networks. Since the audio is close to the 5-minute limit, make sure the file does not exceed 20 MB.
In the request specify the language and ask to put punctuation. The model may not always correctly determine the end of a sentence, especially with fast speech. After generation check that replicas have not merged into one long line. If the interview mentions specific terms (for example, "phishing", "two-factor authentication") add them to the additional field.
Remember: the tool does not perform noise reduction and does not improve speech intelligibility. If the recording contains strong background noise, recognition accuracy will drop. In this case you can try to record the audio again in a quieter room. The tool also does not support automatic splitting into chapters or adding styles — only clean text with markers.
Prompt: "Transcribe interview, language Russian. Add punctuation. Terms: phishing, two-factor authentication. Export to SRT."
Scenario 3: subtitles for a short video in a foreign language
You recorded a 2-minute video in English and want to get subtitles in Russian. The tool supports language selection, but does not perform translation. This means you will get text in English, and then you can manually translate it or use another service. If you need subtitles specifically in Russian, first transcribe the English speech, then translate the text.
In the request specify the audio language — English. The additional field can be left empty if the speech is clear and has no specific terms. After generation you will get SRT with English subtitles. Check that the timestamps match the pronunciation. If the video has proper names, they may be recognized with errors — correct them manually.
The tool does not perform automatic translation and does not synchronize subtitles with video. You can download SRT and load it into a video editor, where there is a translation function or overlay. Note that when translating the text length may change, and markers will need to be adjusted. This is a normal workflow, but it takes time.
Prompt: "Transcribe audio, language English. SRT format. No additional terms."
How to check subtitle quality
After generation open the SRT file in a text editor. Make sure each block contains a number, timestamps in format "00:00:00,000 --> 00:00:05,000" and text. Check that markers do not overlap and do not have negative values. If the audio had long pauses, markers may be shifted — this is not critical, but better fix manually.
Compare text with audio: play the recording and read the subtitles. Pay attention to names, numbers, abbreviations. If the tool made a mistake in a term, correct it. Remember that the model may confuse similar sounding words (for example, "luk" and "lug"). In such cases context helps, but does not guarantee accuracy.
Check file encoding: SRT must be in UTF-8, otherwise Russian characters may display incorrectly. If you plan to upload subtitles to a platform, make sure it supports SRT format. Some services require WebVTT or other formats — in such case convert the file separately. The tool does not perform format conversion between formats.
SRT fragment example: 1 00:00:01,000 --> 00:00:04,500 Welcome to the machine learning webinar. 2 00:00:05,000 --> 00:00:08,200 Today we will consider overfitting and gradient descent.
Limitations and typical errors
The tool is not intended for work with audio longer than 5 minutes or size more than 20 MB. If you have a long recording, cut it into parts and process separately, then manually combine SRT files. Do not try to upload a video file — only audio is accepted. If you have video, extract the audio track in advance.
Speech recognition is not perfect: the model may skip words, add extra or incorrectly put punctuation. This is especially noticeable with poor recording quality, strong accent or presence of background noise. The tool does not perform noise reduction and does not improve intelligibility. If accuracy is critical, consider manual transcription or combined approach.
Do not forget that the tool does not save history and has no integrations. After closing the tab the result will disappear if you did not download it. Copy or download SRT immediately after generation. Also do not rely on automatic language detection — always specify it explicitly, otherwise accuracy may decrease.
Error: MP4 file upload. Solution: extract audio to WAV or MP3 using any converter.
Practical tips for better results
Before uploading make sure the audio has sufficient volume and low noise level. If the recording was made on the street or in a noisy room, try to record again in a quiet room. Use a microphone, not the built-in dictaphone of the phone, if possible. The cleaner the sound, the higher the recognition accuracy.
In the additional field list all specific terms, names and abbreviations that may appear in the audio. This will help the model recognize them correctly. For example, if you recorded a medical lecture, specify "epidemiology, vaccination, immunity". Do not overload the field — 1000 characters is enough for a list of 20–30 terms.
After generation always check the result. Do not publish subtitles without prior preview. If you discover systematic errors (for example, the model constantly confuses two words), try to reformulate the prompt or add context. Remember that the tool does not guarantee ideal result, but significantly saves time compared to manual transcription.
Tip: if the audio has numbers, pronounce them separately or add to terms, for example "2024, 15 percent, three million".
The Subtitles tool is a narrow-focused solution for local audio transcription and SRT file creation. It does not replace professional services with translation and synchronization, but handles the basic task well: turn speech into text with timestamps. Use the provided example prompts as a basis, adapt them to your tasks and always verify the result. Remember the limitations: up to 5 minutes length, up to 20 MB size, no translation and no speaker separation. If you need more, combine the tool with other solutions. The main thing — do not forget to download the ready-made SRT, as the history is not saved.
Open tool: Subtitle generator ↗Interface translations are machine-assisted and may need refinement.