Three Lines: A Haiku Generator with Manual Syllable Checking
Three Lines is a web tool that creates three original haiku based on your description. You fill in three fields: 'Your text or idea', 'Tone, style or format', and 'Length or duration', choose the output language, and click the generate button. The result appears in a separate panel, and you can copy it or download it as a plain TXT file. Below are three fictional scenarios with specific prompts and an analysis of what is useful, as well as an honest discussion about syllable counting and the boundaries of the tool.
Open tool: Haiku generator ↗How the input works and what actually influences the result
The interface is intentionally simple: three text fields, a language selection, and a Generate button. There are no style presets, sliders, or 'level of changes'—all control over meaning happens through the wording in the fields. The first field accepts up to 8000 characters, the second up to 1000. This means you can describe a scene in detail: place, time of day, weather, object, feeling. The more specific the image, the lower the risk of getting generic words like 'silence' and 'wind' without connection to the picture.
The 'Tone, style or format' field sets not the genre but the manner of delivery: restrained, ironic, contemplative, with an emphasis on sound or color. The 'Length or duration' field in the context of haiku works as an indication of volume or density: for example, 'exactly three lines, no title' or 'three short variants in a row'. The tool does not generate audio or video, does not create photorealistic images, and does not send your speech to the cloud: if you use speech synthesis, it is performed locally via eSpeak in WAV format.
It is important to remember: the model can make mistakes, and queue and availability vary. Therefore, treat the first result as a draft, not as a final text. Your task is not to 'click and get a masterpiece' but to set a starting point, check the lines, and reformulate the prompt if necessary.
Field 1: 'Empty railway platform in the rain, early morning, no one around'. Field 2: 'Restrained, without metaphors about the soul'. Field 3: 'Three lines, no title'.
Scenario one: a scene from a trip
Imagine you have returned from a trip and want to capture one moment, not as a diary entry but as a haiku. Describe a specific detail in the first field: not 'beautiful sunset' but 'sunset over the river, boat at the pier, water almost still'. In the second field, ask for a calm, observant tone without direct emotions. In the third—'three lines, each no longer than seven words' or simply 'three lines'.
The useful result here is not a finished poem but three different approaches to the same scene. One variant might build on the contrast of light and shadow, another on the sound of water, a third on the absence of movement. You compare them and choose which detail more accurately conveys your memory. This saves time: instead of an hour searching for words, you get three starting points in one generation.
Checking is simple: read the lines aloud. If the image is clear without explanation and does not fall apart into separate words, the variant works. If abstractions like 'eternity' or 'fate' appear, go back to the first field and add another physical detail: smell, temperature, material.
Prompt: 'Sunset over the river, boat at the pier, water still. Calm observant tone. Three lines without a title'. Check: is there a specific object or action in each line.
Scenario two: urban sound
The second scenario is working with sound. Haiku often rests on a single sound anchor: drops, footsteps, creaking, a horn. In the first field, describe not a picture but a sound scene: 'night city after rain, rare cars, headlights on wet asphalt'. In the second field, specify 'emphasis on auditory images, minimum adjectives'. In the third—'three lines, no rhyme'.
The tool will return three variants, and you can see where sound truly works and where it is replaced by generic words. It is useful to write out all nouns and verbs from the result: if there are specific sources of sound among them, the text is alive. If 'silence', 'peace', 'dream' predominate, the prompt should be refined by adding another sound or surface material.
This scenario well illustrates the tool's limitation: it does not hear your city and does not know local realities. It relies only on what you wrote. Therefore, street names, routes, and specific places are better added to the first field, otherwise you get an averaged image that would suit any city.
Prompt: 'Night city after rain, rare cars, headlights on wet asphalt. Emphasis on sound, minimum adjectives. Three lines without rhyme'.
Scenario three: caption for an image
The third scenario is a short caption for a photograph or drawing. Here it is important not to describe everything visible but to choose one detail. In the first field, write: 'black-and-white photo: bicycle by the wall, long shadow, noon'. In the second field, ask for a 'dry, almost documentary tone'. In the third—'three lines, without addressing the viewer'.
The result is convenient to use as a draft caption: three variants give different angles—shadow, wall, absence of a person. You can take one line from one variant and one from another, but remember that the tool is not intended for assembling text from fragments: this is manual work, and responsibility for coherence remains with you.
Separately about images: Three Lines works with SVG and PNG vectors, but these are vector compositions, not photorealistic generation. If your task is to get a realistic photo, the tool is not suitable for that. For captioning an already existing photo, it is convenient because it does not require uploading the file itself: a text description is enough.
Prompt: 'Black-and-white photo: bicycle by the wall, long shadow, noon. Dry documentary tone. Three lines without addressing the viewer'.
Syllable counting: where certainty ends
Classical haiku in the Japanese tradition is associated with the 5–7–5 syllable structure, but when transferred to other languages, this rule does not work automatically. In Russian, a syllable is a group with one vowel sound, and it can be counted, but stress, contractions, and borrowings make counting ambiguous. In English, the syllable boundary depends on pronunciation: the same word in different speech variants yields a different number of syllables.
The tool is not obliged to produce strict 5–7–5, and the task description explicitly states: explain if strict syllable counting is uncertain in the selected language. This is an honest position. If you write in Russian, check syllables manually by pronouncing the line aloud and marking vowels. If in English, clarify which pronunciation variant you mean, otherwise the count will be disputable.
Practical conclusion: do not demand from the generator mathematical precision that does not exist in the language itself. Better set in the third field 'three lines, rhythm more important than exact count' and evaluate the result by sound. If strict form is essential for you, use the tool as a source of images, and align syllables yourself.
Check: pronounce the line aloud and mark the vowels. If the number of syllables is disputable, note this in a comment to the text rather than presenting it as an exact fact.
How to check the result and what limitations exist
Checking consists of three steps. First: read the three haiku aloud and note where your breathing breaks. Second: underline all abstract words and replace them with concrete details in a new prompt. Third: make sure the lines do not duplicate each other in meaning—three variants should give different angles, not a retelling of the same thing.
The tool's limitations should be known in advance. There is no export to DOCX and PDF, no batch processing, automatic saving, integrations, or OCR in proofreading mode. There are no settings panels, change highlighting, or comparison modes. You cannot publish directly, send by email, or upload documents. There is no premium plan or registration, no voice cloning, photorealistic generation, or audio/video creation. Speech is synthesized locally via eSpeak in WAV, subtitles in SRT, vectors in SVG and PNG.
The limits are also specific: the first field up to 8000 characters, the second up to 1000, speech up to 3000 characters, images up to 4 MB, browser audio up to 20 MB or 5 minutes. Model responses may contain errors, and queue and availability vary. Keep this in mind if you build a regular process on the tool.
Checklist: read aloud, underline abstractions, compare the three variants with each other, check field limits before a long prompt.
How to formulate a prompt to get useful results
The working formula for a prompt is: concrete scene plus one detail plus desired tone. For example: 'empty platform, rain, puddle at the edge, early morning' and 'restrained, without metaphors about the soul'. The fewer evaluations like 'beautiful' and 'sad' in the first field, the more precise the result. It is better to move the evaluation to the second field, where it turns into a tone instruction.
If the result is too general, do not rewrite the entire prompt. Add one physical detail: material, sound, temperature, time. If the result is too literal, remove extra adjectives and leave only nouns and verbs. If the lines turn out identical, ask in the third field for 'three different angles: object, sound, absence'.
And lastly: treat the three haiku as three drafts, not as a finished publication. The tool saves time at the start, but the choice of words, rhythm, and meaning remain with you. This approach is more honest both to the tool and to the reader.
Formula: scene + detail + tone. Example: 'empty platform, rain, puddle at the edge, early morning. Restrained, without metaphors about the soul. Three lines without a title'.
Three Lines is a narrow but useful tool: it gives three haiku drafts from a text description and does not promise more than it can. Fill in the three fields concretely, check syllables manually where the language does not provide an unambiguous count, and remember the limits and the absence of DOCX and PDF export. The three scenarios above are fictional examples, but the logic of working with them applies to real tasks: describe the scene, set the tone, check the result aloud, and refine the text yourself.
Open tool: Haiku generator ↗Interface translations are machine-assisted and may need refinement.