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Random Filler Words Pack
Filler and connector words are easiest to teach — and to audit in your own writing — when they're grouped by function. This generator ships five themed packs of 20 entries each: casual speech ('you know', 'long story short'), formal writing ('notwithstanding', 'pursuant to'), transitions ('however', 'by comparison'), hedging phrases ('arguably', 'it could be argued'), and emphasis words ('undoubtedly', 'crucially'). Pick a theme, set a count, and get a shuffled, duplicate-free selection. ESL instructors build gap-fill and sorting exercises where every word serves the same rhetorical job. Writers pull a transitions pack to vary the connectors in a draft, or a hedging pack to soften an overconfident report. Multi-word phrases stay intact as single list items, so 'at the end of the day' arrives as one entry, not five words. Because each pack is a fixed 20-entry list and batches never repeat an entry, the count effectively tops out at 20 — request 40 and you get the full pack, once through. For longer lists, generate two themes and merge them.
How to use
- Choose your options above
- Click Generate
- Copy your result
Detailed instructions
- Select a theme from the dropdown — choose 'transitions' for essay connectors, 'hedging' for academic softeners, or 'casual' for conversational fillers.
- Set the count to the number of words or phrases you need, keeping it between 6 and 20 for most practical uses.
- Click Generate to produce your themed filler words pack and review the output list.
- Regenerate as many times as needed to get variety, then copy the list directly into your worksheet, document, or codebase.
Use Cases
- •Building ESL gap-fill worksheets where all 12 words target the same cohesive device category
- •Auditing a draft academic essay for missing hedging phrases before submission
- •Seeding a spaCy or Hugging Face NLP corpus with thematically consistent filler language
- •Creating Anki flashcard decks that group emphasis words by register and function
- •Populating a Storybook or Figma prototype with connector-rich prose that reads like real editorial copy
Tips
- →Run the same theme twice and compare outputs — combining two packs gives broader coverage for advanced worksheets without duplicates.
- →Pair the 'hedging' theme with a student's own essay draft to show them exactly which softening phrases they could substitute for overused words like 'maybe.'
- →For NLP training data, generate separate packs per theme and tag each word with its function before injecting it into synthetic sentences.
- →A count of 6 to 8 works best for sorting activities; students should be able to hold the whole set in working memory at once.
- →If you need dialogue that sounds natural, mix words from a 'casual' pack with your character's speech patterns — but limit yourself to two or three per scene to avoid overdoing it.
- →Cross-reference your generated pack against a readability tool after inserting the phrases into real prose — some transitions add length without adding clarity.
FAQ
what is the difference between transition words and hedging phrases
Transitions link ideas across sentences — 'however', 'as a result', 'by comparison'. Hedging phrases soften claims to signal uncertainty — 'arguably', 'it seems that', 'to some extent'. They do different rhetorical jobs, so the packs keep them separate for teaching or editing one function at a time.
how many filler words should I generate for a classroom worksheet
Eight to twelve suits most gap-fill or sorting activities — enough variety to challenge students without overwhelming them. Drop to six for beginner ESL learners. For advanced academic writing classes, generate a transitions pack and a hedging pack separately so students practice distinguishing the two functions.
why does the pack stop at 20 items
Every theme is a hand-written pool of exactly 20 words and phrases, and a batch never repeats an entry, so 20 is the ceiling even though the count field accepts 40. For a longer list, generate two themes — transitions plus hedging is a natural pairing — and merge the results.
can i use filler word packs for NLP or synthetic text work
Yes, with the right expectations: these are fixed curated lists, not a corpus, so they work as seed vocabularies or slot-fill options rather than training data at scale. Multi-word entries like 'at the end of the day' arrive as single items, which keeps phrase boundaries intact when you feed them into templates.
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