6 ms·
Introducing Google Cloud Natural Language API, Speech API and New Data Center
- a3camero 10y agoFree till August 1st (with request limit) and then there'll be a free tier. Pricing is here: https://cloud.google.com/natural-language/pricing https://cloud.google.com/natural-language/pricing
- shimon_e 10y agoluis.ai is 100k requests free per month vs Google's 5k.
- spdustin 10y agoRegarding non-streaming transcription: It doesn't seem like the return includes timings, which would limit its usefulness in transcription for accessibility (where, for example, a post-processing step on our side would consume the Cloud Speech API and build SRT subtitle files for class recordings) Is there a product / service / library out there that could help align a known-good transcript with the original audio (creating the timings) if the Cloud Speech API doesn't plan to return timings?
- nolite 10y agoWhy would you need the Speech API if you already have a known-good transcript?
- spdustin 10y agoI'm sorry if I was unclear. If I used the Cloud Speech API to produce the transcript, is there another library/service/etc that would align it to the original audio again.
- taf2 10y agoWatson does this, VoiceBase does this and I believe HP and MS do this... it's very common for speech API's to provide time offset information for each word.
- nmcfarl 10y agoSpeechmatics sells this product. My company, CastingWords, uses it to align our human produced transcripts, and make SRTs. It works well.
- danso 10y agoYeah that was a bummer to see in the alpha and I was holding out that they'd expose that data at release date (as IBM Watson has), but maybe they want to limit the ability for competitors to easily appropriate the sound-to-transcribed-word data.
- spdustin 10y agoThanks for mentioning Watson; I keep meaning to go back to it and see how limits have improved.
- skoocda 10y agoI'm currently developing a system along those lines. Not publicly available quite yet, but should be soon. Bug fixing at the moment.
- nshm 10y agoYou can use Speechmatics directly
- ljoshua 10y agoOn the other side of the NLP spectrum, what players out there are involved in NLG (natural language generation)? I've seen Arria and a couple other small projects, but I'm just starting to investigate the space and haven't found a whole lot yet.
- ganeshkrishnan 10y agoWe are working on pre-processing text corpus to generate assumptions and presuppositions using NLG. Our initial aim is to index the whole Wikipedia and have pre-generated NLG for all pages as additional info for better searches. Right now we are using Lucene & Syntaxnet but I haven't found a good library for hierarchical clustering of text Check us out at www.shoten.xyz
- ammaristotle 10y agoCheck out Wordsmith by automatedinsights.com - it does NLG for Yahoo! Fantasy Football, among other places.
- zyxley 10y agoSo how long until these new services get summarily discontinued?
- rabidrat 10y agoSeriously, there's no way I would use Google APIs for anything production at this point.
- bitmapbrother 10y agoWell, if you want uptime that's better than AWS then I would.
- bitmapbrother 10y agoLet me guess, still upset about Google reader?
- eva1984 10y agoEnterprise should be treated differently if the ever wants to tackle AWS.
- brazzledazzle 10y agoBetween negative comments about Google's service lifecycle, choice of font/colors on a page and general nitpicking of every little detail on a linked page or someone's comment I'm getting fed up. It's gratuitously negative and repetitive to see this kind of stuff every day. If I wanted that kind of negativity and snideness I'd be using reddit. Maybe some kind of "meta" comment section is the solution so we can have discussions about or derived from the content in one section and the folks that want to bash the company/person/font/colors/title/grammar/credentials/etc. can use the other.
- Teodolfo 10y agoYou can read the terms of service here: https://cloud.google.com/terms/ https://cloud.google.com/terms/ They include a deprecation policy.
- alyx 10y agoSimilar offering suite from Microsoft, https://www.microsoft.com/cognitive-services/ https://www.microsoft.com/cognitive-services/
- euyyn 10y agoI wonder how they compare.
- jaytaylor 10y agoAFAICT, the MS offering looks pretty basic by comparison [0]. No named entity recognition or sentiment analysis. [0] https://www.microsoft.com/cognitive-services/en-us/linguistic-analysis-api https://www.microsoft.com/cognitive-services/en-us/linguisti...
- alyx 10y agoThrough a combination of cognitive API sentiment analysis and entity recognition is also supported. https://www.microsoft.com/cognitive-services/en-us/text-analytics-api https://www.microsoft.com/cognitive-services/en-us/text-anal...
- singham 10y agoOpen Calais has been there for quite some time
- vonnik 10y agoI'm curious to see whether clients actually want to move very large datasets through these APIs, or whether that's too costly. It strikes me that cloud services work best for data generated and managed in the same cloud...
- matt4077 10y agoI've been moving into the (google) cloud and one of the main benefits is that I no longer have to down- and (especially) upload the data I work with, but simply remote-control a pipeline with a much larger pipe. I guess for data that is generated on site it's a net negative, but I'd guess almost all data has to go across the internet at some point and google is probably not the worst warehouse on that highway.
- melvinmt 10y agoSo about $1.44 per hour, that's reasonable-ish.
- ganeshkrishnan 10y agoWe run Apache OpenNLP which gives comparable results to this service. The advantage of Google Natural Language right now is the Wikipedia link it provides to the entities it detects but I haven't seen it's results beat Open NLP
- IshKebab 10y agoHe's talking about the speech recognition. Google's speech recognition is far ahead of the competition, and also slightly cheaper (except for Baidu's which is free, but good luck getting it to work).
- nostrademons 10y agoAccuracy still seems to leave a fair bit to be desired. For example, when parsing "Blue, Brown, Orange, Green and Red Lines were running normally" from this news article [1], "Blue" was interpreted as the color [2], "Brown" was interpreted as the Brown Bears football team [3], "Orange" was interpreted as the Orange Line Washington (not Chicago) Metro [4], "Green" was interpreted as "environmentally friendly" [5], and "Red lines" was interpreted as the organization (but without a Wikipedia page). Works pretty well on places, though. [1] http://chicago.cbslocal.com/2011/02/02/dangerous-blizzards-wrath-continues/ http://chicago.cbslocal.com/2011/02/02/dangerous-blizzards-w... [2] http://en.wikipedia.org/wiki/Blue http://en.wikipedia.org/wiki/Blue [3] http://en.wikipedia.org/wiki/Brown_Bears_football http://en.wikipedia.org/wiki/Brown_Bears_football [4] http://en.wikipedia.org/wiki/Orange_Line_(Washington_Metro) http://en.wikipedia.org/wiki/Orange_Line_(Washington_Metro) [5] http://en.wikipedia.org/wiki/Environmentally_friendly http://en.wikipedia.org/wiki/Environmentally_friendly
- bduerst 10y agoHmm, which NLP request did you run it as? It seemed to run better when I ran it through analyzeEntities: http://pastebin.com/raw/AfXvKAzw http://pastebin.com/raw/AfXvKAzw
- nostrademons 10y agoIt was in context - I pasted the whole text of the CBS Local article I linked to into the "Try it out!" text field on the product home page, and these were the entities it identified.
- dmorr 10y agoGoogle Research PM here -- my team built the language understanding tech that powers the API. Thanks for checking it out! You picked a really interesting, and really hard, sentence to use to test us with. It has a couple of interesting phenomena: a reduced conjunction ("Line" goes with each color to make a name, like "Blue Line" even though "Blue" and "Line" are far apart), and high ambiguity ("Green" could be the color, the environmental movement, the political party, one of several people, or lots of other things (https://en.wikipedia.org/wiki/Green_(disambiguation) https://en.wikipedia.org/wiki/Green_(disambiguation) ). These are hard! So hard, in fact, that I'm reasonably sure that there's no system in existence that would get these ones right. (I hope I'm wrong, actually, I'd love to see approaches that can solve problems like this generally.) Our systems are state-of-the-art, or in some cases better than any other published system. But language is really hard, and even the world's best systems are way worse than any human at understanding language. That's what makes working on this stuff so much fun and so challenging. It feels so easy for us as humans, but we just haven't figured out how to model all this so that the computers can do as well. (I'm going to steal this sentence to use internally as a great "NLP is hard" example, thanks!)
- ImTalking 10y agoIs this technology good enough to be able to have a relatively intelligent 'conversation' with a real person?