aw-toh-kaw-ruh-LAY-shuhn
/ˌɔː.toʊˌkɔɹəˈleɪʃən/
autocorrelation is pronounced aw-toh-kaw-ruh-LAY-shuhn (/ˌɔː.toʊˌkɔɹəˈleɪʃən/). Autocorrelation is a statistical measure that describes how a signal correlates with a delayed version of itself as a function of delay. It helps identify repeating patterns or periodicity within a time series, such as in signal processing or econometrics. The term combines 'auto-' meaning self and 'correlation,' emphasizing self-similarity over time.
Autocorrelation is a statistical measure that describes how a signal correlates with a delayed version of itself as a function of delay. It helps identify repeating patterns or periodicity within a time series, such as in signal processing or econometrics. The term combines 'auto-' meaning self and 'correlation,' emphasizing self-similarity over time.
"The autocorrelation of the audio signal reveals its repeating waveform."
"Researchers used autocorrelation to detect periodicities in climate data."
"In time-series analysis, a strong autocorrelation at lag 1 indicates high persistence."
Say aut-o-co-rr-e-la-tion with primary stress on the fourth-to-last syllable: /ˌɔː.tə.kɔˈreɪˌleɪ.ʃən/ (US/UK). Break it into parts: AUTO- co rRE LA- tion. Start with /ˈɔː/ as in 'awe', then /tə/ (reduced), /kɔ/ as in 'cot', then /ˈreɪ/ (like ‘ray’) and /ˌleɪ.ʃən/ ending. Ensure the 'rr' is not a trilled American-style r; keep a single American r sound, with a light, non-syllabic 'l' sound leading into 'eɪ'. Audio reference: imagine saying auto + correlation, but emphasize the 'reɪ' syllable before the final 'ʃən'.
Two common pitfalls are: (1) Misplacing the stress, saying ‘author-CO-rrelation’ or distributing stress too evenly. (2) Slurring the -la- into -la-tion, producing /ləˈleɪ.ʃən/ instead of the clean /ləˈreɪ.lə.ʃən/. Correction: practice the sequence auto- (ˈɔː.to) then co-rre-la-tion with clear /rə/ to avoid an extra syllable merge. Focus on vowel lengths: keep /ɔː/ long and avoid reducing the /eɪ/ in the central syllables. Finally, ensure the /t/ remains crisp, not flapped in American casual speech.
In US English you’ll hear /ˌɔː.tə.kɔˈreɪ.leɪ.ʃən/ with full rhotic r and moderate vowel lengths. UK English often stresses slightly differently and may reduce certain vowels, giving /ˌɔː.tə.kɒ.rəˈleɪˌʃən/. Australian tends toward /ˌɔː.tə.kɔˈreɪləˌʃən/ with non-rhotic tendencies softening r unless followed by a vowel. The core is the /ˌɔː/ at the start and the /ˈreɪ/ in the middle-right chunk; the final -tion remains /ʃən/. Focus on ensuring the middle syllables carry the intended weight and the final /ˈleɪ.ʃən/ remains distinct.
It combines multiple phonetic features: a long initial vowel cluster /ˈɔː/ that can be reduced in fast speech, the mid consonant sequence /tə.kɔ/, and the salient /ˈreɪ/ followed by /ləˈʃən/. The challenge is maintaining clear syllable separation across the mid-stem while keeping natural rhythm and not merging the -co- with -rr- or biasing the -la- into -lə- before the -tion. Practice with slow, deliberate enunciation and then increase tempo while preserving each segment’s timing.
Yes: the sequence -co- + -rre- matters. Some speakers blend /kɔr/ into /ˈkɔr/ or misplace the primary stress between the -re- and -la- syllables. To master it, stress the /ˈreɪ/ syllable just before -la-tion and keep the /r/ sound distinct from the preceding /t/; avoid flapping /t/ into a soft d-like sound in US casual speech. Clear, deliberate articulation of each morpheme helps the word stay intelligible in technical contexts.
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Autocorrelation derives from auto- (self) + correlation, via late 19th/early 20th century mathematical statistics terminology. The prefix auto- comes from Greek autos meaning ‘self, same’, used in many scientific terms to denote self-action or self-reference. Correlation stems from Latin correlatio, from correlare (to relate), with cor- (together) and latus (side, bearing). The term first appeared as statistical jargon in the early 20th century as researchers formalized how a signal relates to itself at different time lags. The concept evolved from cross-correlation methods used to compare two signals to the specialized idea of autocorrelation to assess internal structure of a single time series. In practice, autocorrelation became central in fields like econometrics, meteorology, and engineering, informing models of persistence, seasonality, and spectral content. Early pioneers include mathematicians and statisticians who extended correlation measures to lagged observations, culminating in the autocorrelation function (ACF) widely used in time-series analysis. The word has become common in signal processing, climate science, finance, and neuroscience, where self-similarity and periodicities are essential features of data.
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Words that rhyme with "autocorrelation"
-ion sounds
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