Lirix – computational linguistics aspects

In my last update on applied computational linguistics, I have written about PodZinger that uses speech recognition to figure out which advertisement to match to the podcast you are searching with their service.

Another company is claiming to do that with songs – Lirix. Their upcoming AdLirix platform is supposed to be so effective that Lirix would be able to give away songs for free and make back the income by embedding well-targeted advertisements.

The devil of course is in details – many songs have so little meaning in them, that it might be a trial to even figure out what they are about manually, never mind automatically at the volume required to fill an attractively large catalog.

Their DEMOFall presentation did not go into that level of details, so I emailed some questions to Lirix people directly. They promptly replied with an example:

…, here’s a lyrical excerpt from a hiphop song named “How We Do” by a rapper named “The Game”. (This song was a big radio hit last year.)

“I put Lamborghini doors on the Escalade
Low-pro so it looks like I’m riding on blades”

In this case, we would tag the specific words “Lamborghini” and “Escalade”, the phrase “low profile”, and the themes “high-end automotive”, “after-market automotive”, and “bling”.

This looks quite advanced, if the algorithm uses true computational methods. Unfortunately, I have doubts that it does.

I can see how Lamborghini could be matched to the high-end automotive subject (named entity recognition, clustering, even database-lookup). I have no idea how they would also connect the sentence above to the after-market automotive.

I suspect that behind the scenes, Lirix will be doing a lot of manual categorisation. I asked my contact about this issue and got the reply that effectively said “good question – no answers at this stage”. Fair enough. If they can do it automatically, they have a strong competitive advantage; if they cannot do, this may mean they cannot scale fast. Either way, they may have a reason to keep quiet for now.

We will wait and see. I imagine the competition for making money from ‘free(ish)’ songs is heating up. Many techniques will be tried and Natural Language Processing algorithms may prove to be important for the successful business.