## 7 – Sakoe Chiba Bounds

Let’s suppose we have two signals that really are not that similar. Dynamic time warping could allow them to match much better than they should. Look at this example where we use a different shorter signal along with the same long one as in the last example. >> Okay. >> While I have to start … Read more

## 6 – Dynamic Time Warping

Okay, so all dynamic time warping is doing is trying to align the samples between two whistles we’re comparing so that they best match up. >> Yep, let’s line up the two signals we are trying to compare on the x and y-axes. That will allow us to more easily see how we are matching … Read more

## 5 – Euclidean Distance Not Sufficient

You always say do the simple thing first and add intelligence only if necessary. What happens if we just do Euclidean distance here? >> Let’s try it and find out. Here are some reasonable delta frequency numbers for the top and bottom graphs. >> The top time series has 21 samples, but the bottom one … Read more

## 4 – Warping Time

That will help our recognizer handle the whistles no matter what frequency they start at. Next let’s work on the time warping. >> Just to be clear you’re talking about the problem where I could draw out your name saying Fad or say your name quickly like Fad. >> Yep, that’s precisely the problem we … Read more

## 3 – Problems Matching Dolphin Whistles

That problem is going to be the focus for this lesson. We need to be able to handle classes of signals, where each example may be warped in time a bit differently. >> Okay, well, for features, can we just use the whistle frequencies through time? >> Normally, that would be a good idea, but … Read more

## 2 – Dolphin Whistles

Let’s start with a problem I’m currently exploring, dolphin communication. Here’s a spectrogram of a dolphin whistle. In actuality, dolphins have several types of vocalizations, including burst pulses and echolocation, but whistles are the easiest to see in a spectrogram. >> First, let’s talk about what a spectrogram is. On this spectrogram, the x-axis is … Read more

## 1 – Pattern Recognition through Time Intro

Thad, we’ve covered a lot of different machine learning algorithms. But what about situations where we have time series? >> You mean like speech recognition? >> Yeah, I know you’ve worked in sign language recognition and handwriting recognition. They seem to be similar problems. >> Yep, they are. Pattern recognition through time is one of … Read more