AI engineering glossary · Time series recsys
What is DTW (dynamic time warping)?
Dynamic time warping (also called DTW): A method for measuring similarity between two sequences that may run at different speeds, by finding the alignment that stretches or compresses time to minimise the total difference. It is used for matching patterns in signals and speech.
Dynamic time warping: an example
Two recordings of the same word, one spoken slowly, still match well under it.
Related terms
- Time series
- Autocorrelation
- Anomaly detection (time series)
- Nearest neighbour
More Time series recsys terms
- ETS model
- Exogenous variable
- Exponential smoothing
- Factorisation machine
- Forecast horizon
- Forecast reconciliation
- Forecasting
- Fourier terms
Where you learn it
Dynamic time warping is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.