Identify and count speech fillers and hesitations. Reports frequency and patterns of words like 'um', 'uh', 'like'. Offers suggestions for improvement.
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Filler Word Detector is an AI-powered tool that identifies and counts speech fillers and hesitation patterns in audio recordings. It detects common filler words like 'um', 'uh', 'like', 'you know', 'so', 'well', and other hesitation patterns, reporting frequency and usage patterns. The tool analyzes speech to identify all instances of filler words, counts the frequency of each type, calculates overall filler word rate, and notes patterns in their usage. It provides detailed feedback on filler word usage with suggestions for reducing fillers if they occur frequently. This makes it valuable for public speakers improving their delivery, professionals refining presentation skills, students developing speaking abilities, or anyone wanting to reduce filler words and speak more confidently and clearly.
Upload your speaking audio and the AI analyzes speech for filler words and hesitation patterns systematically. It identifies all instances of common filler words including 'um', 'uh', 'like', 'you know', 'so', 'well', 'actually', 'basically', and other hesitation markers. The tool counts the frequency of each filler word type, calculates the overall filler word rate (fillers per minute or per 100 words), identifies patterns in filler word usage (when and where they occur), and notes hesitation patterns beyond just words (pauses, repetitions, false starts). The analysis provides detailed statistics showing which filler words are used most frequently, when they tend to occur (beginning of sentences, transitions, etc.), and overall usage rate. It offers specific suggestions for reducing filler words, such as pausing instead of filling silence, preparing transitions in advance, and practicing smoother speech flow. You can specify particular filler words to track in the notes field.
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