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Show HN: Lexika – Search Engine for Spoken Words/Phrases in YouTube Videos

85 points| stephensonsco | 10 years ago |lexika.io

33 comments

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[+] tsurantino|10 years ago|reply
YouTube actually had something like this available for a while (or still does this?) through Caption Search.[1] If a video had captions available (either user provided or automated), one could search based on the captions on that video. Results would return the video and the time associated with that clip in question.

I am not exactly sure why they discontinued the user experience, since it seems like it could be really useful for finding relevant parts in potentially long videos.

[1] http://youtube-global.blogspot.ca/2012/02/captions-for-all-m...

[+] stephensonsco|10 years ago|reply
Yeah, good point. We knew about this but the accuracy wasn't all that great. Our algorithm is fuzzy and can find results even if they are transcribed incorrectly (even today, every speech transcription technology out there still makes plenty of mistakes).
[+] tonydiv|10 years ago|reply
I would love to contact you regarding using this for sales phone calls. Often times, my employees don't remember an important portion of some conversation. This makes it really easy to find that!

tonydiepenbrock[@at]gmail.com

[+] mkorfmann|10 years ago|reply
Me too!

manu <at> korfmann <dot> info

[+] pmorici|10 years ago|reply
Will this work with videos that aren't already subtitled? I haven't gotten one without subtitles to work yet maybe I'm just not waiting long enough though.
[+] stephensonsco|10 years ago|reply
We do two things simultaneously. If there is no closed caption, then the video is submitted to our API to be processed (which takes longer on longer videos - a link shows up on the page to let you know the future URL). If there is a CC, then we parse that right away (which gives ok search results) but still submit to our API for processing, so later the search results will purely be from our indexing.
[+] fiatmoney|10 years ago|reply
This only works if you know the particular youtube video the phrase appears in.

Scraping the content would be more useful, but I'm guessing that gets shut down quick.

[+] stephensonsco|10 years ago|reply
You are right that you need to input the particular video for now, but we are expanding to include multi-video search (constantly indexing in the background). Right now the use case is particularly nice for finding phrases in long videos (look for Donald Trump saying random stuff {wall, tremendous, many many, women}, it is pretty comical - e.g. http://www.lexika.io/?s=https%3A%2F%2Fwww.youtube.com%2Fwatc...).
[+] jjzhang|10 years ago|reply
A heads up on the homepage, the video you featured Steve Carrell and Jimmy Fallon with the keyword "pantaloons" is captioned as "the wrong kind pantaloons ah", when the spoken phrase was "the wrong kind of pantaloons on" - maybe this is me being paranoid and pedantic, but I feel like having a featured video with a pre-selected keyword that returns flawed captions gives a worse impression than just having the video flags without any captions at all. I understand you guys are still refining the product but highlighting one of your flaws (however small) so early on can rub people the wrong way.

On a separate note, when I google "lexika search engine" I get your old homepage lexika.co instead of the one linked here, lexika.io. Consider setting up a redirect from .co to .io?

[+] stephensonsco|10 years ago|reply
Thanks for the transcription feedback. You can look at this as a problem but we think it's a cute demonstration of our search ability. We didn't really set out to make transcriptions perfect (that's very, very hard), we wanted to make search very accurate. Having a better transcription model would be great though (we are working on that!).

We'll definitely work on the site. (We should have done that earlier.) Thanks again!

[+] mrborgen|10 years ago|reply
Nice service! May I ask what machine learning technology you're using? I'm experimenting with neural nets these days, in order to learn the basics of image & speech recognition and would love to hear about your experiences if your'e usikg ANN's.
[+] stephensonsco|10 years ago|reply
You've got it. Deep neural networks are currently the best performers when doing automatic speech recognition.
[+] chejazi|10 years ago|reply
YouTube is a huge domain - the potential for audio indexing could bring vast improvements to search relevancy. What other audio domains are you experimenting with?
[+] stephensonsco|10 years ago|reply
The first thing that comes to mind is podcasts. That are a slightly different direction, but a great fit for our service. They're long, have well spoken words, and are regularly released, so there is a mound of searchable audio data out there just waiting to be liberated.
[+] bedeho|10 years ago|reply
Really well executed product in the 'why doesn't this exist already' category!
[+] misiti3780|10 years ago|reply
I love this idea - can you shed any light on the technologies you are using?
[+] stephensonsco|10 years ago|reply
Yeah for sure! This site is basically a demo/test for our backend.

We built an API that processes audio and forms an index for that file. The API search function then goes into that index to look for queries. It doesn't just look for words that match the text you see, but also the way it sounds.

[+] avodonosov|10 years ago|reply
the Search button is absent (on a mobile chrome). Only the text field. How to submit a request?
[+] stephensonsco|10 years ago|reply
You should be able to hit enter in the search field on your phone's soft keyboard (or the button might just say search). Which phone/operating system is this?
[+] Hydraulix989|10 years ago|reply
Could this be used for subtitling videos? I have a lot of anime VHS tapes in Japanese.
[+] stephensonsco|10 years ago|reply
Ah, that would be really nice to do. Our speech transcription only does English at the time but we definitely have our eye on other languages.
[+] Kinnard|10 years ago|reply
What's next after indexing and search?