It's truly amazing how the world's most difficult and high maintenance people expect the world yet aren't willing to pay a fair price for their high standards. This is definitely the case in the following text exchange between a dog sitter and a prospective customer.
It seems that Junie's owner thinks she is doing a favor paying $110 for a week of dog sitting - while expecting the dog sitter to be with the dog 90% of the time. And administering complicated medication. The texts are absolutely infuriating, especially when it becomes clear that the prima donna isn't getting what she wants. Don't be like Junie's dog mom. Treat people with respect. Most of the comments on the poor dog sitter's post agree with us.
If you're not familiar with "flower crowns", they're usually worn by hippies or brides. Most recently though, they've made an appearance at music festivals like Coachella.
While dogs aren't usually allowed at music festivals, if they were, you'd find all of these pups waiting in line to meet their favorite band.
Henry Conklin loves his dog and wants to share the canine's voice with the world. Modern social media and Conklin's technological know-how make that possible.
The mathematics/computer science undergraduate student at the University of Virginia regularly engages in competitive programming and decided to use these skills to make a Twitter account that his dog Oliver could 'control'.
@OliverBarkBark tweets every time Oliver barks.
By connecting a Rasberry Pi, a wifi dongle, and a microphone, I was able to make a system that automatically detected, filtered, and published each and every one of Oliver's deafening vocalizations.
The full process from bark to tweet takes three steps. First is recording. I have the raspberry pi listening continuously and triggering a recording once it hears a sound over a preset volume. Oliver barking is by far the loudest thing within several miles, so the volume threshold should be sufficient. However, the recordings are still triggered occasionally by unwanted junk. To guard against this, I needed to perform a second step to filter the barks from the junk.
I took a machine learning approach to filter out the barks. I built a model using the pyAudioAnalysis library and around a day's worth of barks (about 20). I then set up a bash script to run every ten minutes, classify each recorded sound, and forward the barks on to the next step.
Finally, the barks are forwarded to the twitter api (using python-twitter) and posted under the handle @OliverBarkBark (be sure to follow!). Currently the tweets are random strings composed of "bark," "ruff," and "woof." I plan to replace that with a bark-to-text translator that will likely produce similar results but be more accurate to Oliver's actual voice.
Being the cool guy that he seems, Conklin also made all the code it took to accomplish this publicly available.
He said the next step is puppy podcasting.