We used to have someone go into a recording studio to record speech for our software. Recently, the Google Cloud has become good enough so that we are considering to use the API instead. We went through the terms, and it seems that distributing the WAV results is not covered by the terms. Does anybody know if this is okay?
I'm curious what exactly means "distributing the WAV results" for you.
In GCP all the data you upload or generate is owned by you according to security policy. It is not accessible for anyone else than you, unless you explicitly grant access. So, in this case once you obtain the audio result from Text-To-Speech you decide how to distribute it.
Related
I need to transcribe a large number of Handwritten documents. I tried to use cloud services from either Google, Amazon, and Microsoft. Namely:
https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/
https://cloud.google.com/vision/docs/handwriting
https://aws.amazon.com/textract/
Unfortunately, none of them achieved good enough results. I suspect it is because my documents have a weird handwriting style, and as a result, the networks struggle a lot.
I searched whether I could fine-tune (with manually transcribed data), but I have not found anything online, so as a last resort, I ask here.
If it is possible to fine-tune one of these models, could you please point me some resources?
You are correct, with Azure Cognitive Services with Computer Vision you cannot upload your own data to train the API to recognise the handwriting in your documents I'm afraid. I can't comment on the other offerings from AWS and Google I'm afraid, but certainly not for Azure.
Bottom Line: Cloud Run and Cloud Functions seem to have bizarrely limited bandwidth to the Google Drive API endpoints. Looking for advice on how to work around, or, ideally, #Google support to fix the underlying issue(s) as I will not be the only like use case.
Background: I have what I think is a really simple use case. We're trying to automate private domain Google Drive users to take existing audio recordings and send them off to Speech API to generate a transcript on an ad hoc basis, and to dump the transcript back into the same Drive folder with email notification to the submitter. Easy, right? Only hard part is that Speech API will only read from Google Cloud Storage, so the 'hard part' should be moving the file over. 'Hard' doesn't really cover it...
Problem: Writing in nodejs and using the latest version of the official modules for Drive and GCS, the file copying was going extremely slow. When we broke things down, it became apparent that the GCS speed was acceptable (mostly -- honestly it didn't get a robust test, but was fast enough in limited testing); it was the Drive ingress which was causing the real problem. Using even the sample Google Drive Download app from the repo was slow as can be. Thinking the issue might be either my code or the library, though, I ran the same thing from the Cloud Console, and it was fast as lightning. Same with GCE. Same locally. But in Cloud Functions or Cloud Run, it's like molasses.
Request:
Has anyone in the community run into this or a like issue and found a workaround?
#Google -- Any chance that whatever the underlying performance bottleneck is, you can fix it? This is a quintessentially 'serverless' use case, and it's hard to believe that the folks who've been doing this the longest can't crack it.
Thank you all in advance!
Updated 1/4/19 -- GCS is also slow following more robust testing. Image base also makes no difference (tried nodejs10-alpine, nodejs12-slim, nodejs12-alpine without impact), and memory limits equally do not impact results locally or on GCP (256m works fine locally; 2Gi fails in GCP).
Google Issue at: https://issuetracker.google.com/147139116
Self-inflicted wound. Google-provided code seeks to be asynchronous and do work in the background. Cloud Run and Cloud Functions do not support that model (for now at least). Move to promise-chaining and all of a sudden it works like it should -- so long as the CPU keeps the attention it needs. Limits what we can do with CR / CF, but hopefully that too will evolve.
I'm working on a project where I am tasked to use google cloud services to process and visualize fitness data. For example, I have exported some apple health data from my watch, and it is in .xml format. From a high level, I envision this .xml file starting off in object storage, and being converted to .csv through a cloud function (triggered by the creation of the .xml object in storage) and stored again in object storage (different bucket). Then I see these .csv files being processed by a DataFlow pipeline, which will reformat the data to the template schema that I would like the data to be organized with. This pipeline will output the resultant .csv to BigQuery, which will then be designated as a data source for Data Studio. I will then configure Data Studio to produce some simple reports that compare the health data to recommended values. I would like for this report to be accessible as a .pdf in object storage potentially as well. Am I on the right track, or am I missing some key services to accomplish this?
Also, I'm new to posting on StackOverflow, so if this question is against the rules or not welcome, please let me know.
Any feedback is greatly appreciated, as I have not been able to bounce these ideas off of other experienced cloud architects/developers.
This question is currently off-topics by the rule of StackOverflow, as it does not contain any problems to resolve. See point 4-5.
As a high-level advice, I do not see why it should not be possible based on the services you mentioned but you would need to implement it and try it on your side and evaluate the features of each service in your workflow.
In terms of solution or architecture advice, those are generally paid services and you would most likely find little help here for those unless you have a specific problem to solve with said services. You might find some help on the internet as well. ie.Cloud Solutions, Built it on GCP, etc
You might find this interesting to review as well as it mimics your solution. Hope this helps.
I wanted to dive into the world of distributed systems, cloud computing, IoT, etc., and I gotta be honest, I imagined everything being a little more intuitive than it finally turned out.
I had a tiny testing architecture in mind, that I'd like to set up with Google Clouds and their services, but I am kinda stuck since I can't get my head around some concepts.
What I basically wanted to do (as a first step) is writing a simple java application that would run locally on my computer. This application should just generate random numbers and send those numbers somehow to the google cloud. On the cloud I wanted to define another java application that would manipulate those random numbers in some kind of way (it doesn't matter actually). Afterwards, the output should somehow get back to me of course. And actually, at the moment, I don't even care about how exactly. It could be somehow back to my local app (with some kind of listener, would that be possible?). But it could also simply store the results somewhere on the google cloud? Or maybe upload them to my google drive?
I guess you already noticed that - at some points - I don't even know what i want exactly, since I'm not sure of what is possible, and what not.
Could you provide me some help to get this set up?
The most important questions for me right now are:
Do I need to use a pubsub system, where my generated numbers are sent
to, and which then forwards this to the cloud app, that transforms my
data?
How do I get my data from the local app to the cloud services?
Would my data transforming app run on Google Dataflow?
Above I wrote "as a first step"... because later I would also like to send config files (for example in json format, or xml) to the cloud, and the
cloud application should transform those config files... if I get the
first scenario running the I guess this woul also be no problem
right?
Those are just a few of the questions that are on my mind currently. The most important ones I guess.
It would be a big help. Sorry, if the questions are not very precise, but I really need some kind of pointing into the right direction.
Thank you in advance!
I think it would be good to read up on some of the technologies you mention here:
Google Cloud Pubsub: Pub/Sub enables you to publish messages to a topic, and consume them in another place in the (Google) Cloud. You can see some different examples of publishers and consumers in the link. In your case you could for example write a Java application that writes random numbers to the Pub/Sub queue, where they will sit for 7 days to be consumed by another component (for example, Google Cloud Dataflow). To get started developing, you can find the SDKs here (there is a Java SDK).
Google Cloud Dataflow is managed service running Apache Beam pipelines to process your data at scale. You can learn about the different concepts here and get started designing your pipeline here. I suggest taking a look at some examples first though, which will make it more easy to grasp what is actually going on. Dataflow has a PubSub connector, so in your application you will be able to read from the topic you created before. In Dataflow you can for example multiply all your random numbers and write them to a certain sink (for example Google Cloud Storage, or even BigQuery or PubSub again).
Google Cloud Storage: is a cloud storage where you can put files, for example the output of your Dataflow pipeline. You will be able to manually download the files using the Cloud Console UI, or you can use one of the SDKs to download the output programmatically.
Hope this gives you an overview and some pointers to start. Whenever you are ready and have a more concrete use case in mind, you can start looking at some more components.
I'm planning to use Google Vision for document recognition.
For example, I will upload driver license and I should get all text data and verify that it is driver license and not the cover of a magazine.
The question is: does Google Vision has API for deletion of uploaded images?
Does Google Vision fit my case if I have some security requirements?
If you use Google's mobile vision API, text and face detection is done on device rather than being uploaded:
https://developers.google.com/vision/
For those who wondering the same problem, You can check their data policy here.
https://cloud.google.com/vision/docs/data-usage
My reading of Google APIs Terms of Service indicates that you will not be able to delete the images.
5b. Submission of Content
Some of our APIs allow the submission of content. Google does not acquire any ownership of any intellectual property rights in the content that you submit to our APIs through your API Client, except as expressly provided in the Terms. For the sole purpose of enabling Google to provide, secure, and improve the APIs (and the related service(s)) and only in accordance with the applicable Google privacy policies, you give Google a perpetual, irrevocable, worldwide, sublicensable, royalty-free, and non-exclusive license to Use content submitted, posted, or displayed to or from the APIs through your API Client. "Use" means use, host, store, modify, communicate, and publish. Before you submit content to our APIs through your API Client, you will ensure that you have the necessary rights (including the necessary rights from your end users) to grant us the license.
Being able to "publish" your driver's licenses is probably not something you want.
The above terms are also completely at odds with the GDPR where the user has the right to delete and modify their data.
7a. Google Privacy Policies
By using our APIs, Google may use submitted information in accordance with our privacy policies.
Note that those privacy policies are the ones that govern normal users, not cloud specifically. In plain text, and IANAL, it means that Google assumes that for whatever content you give them, the user has agreed to anything that Google does for a user that directly use, say Google Docs.
That's another indication that it's impossible to use their APIs and be GDPR compliant.
This should solve your issue
tl;dr "The stored image is typically deleted in a few hours."
Will the image I send to the Cloud Vision API, the results or other
information about the request itself, be stored on Google servers? If
so, how long and where is the information kept, and do I have access
to it? When you send an image to Cloud Vision API, we must store that
image for a short period of time in order to perform the analysis and
return the results to you. The stored image is typically deleted in a
few hours. Google also temporarily logs some metadata about your
Vision API requests (such as the time the request was received and the
size of the request) to improve our service and combat abuse.
Some of the other answers a bit outdated so adding my own answer. The data usage FAQ states
When you send an image to Vision API, we must store that image for a short period of time in order to perform the analysis and return the results to you. For asynchronous offline batch operations, the stored image is typically deleted right after the processing is done, with a failsafe Time to live (TTL) of a few hours. For online (immediate response) operations, the image data is processed in memory and not persisted to disk.
If you use the synchronous Vision API methods, the image is never persisted in Vision API and so there is nothing to delete. If you use the asynchronous Vision API methods, the image is only persisted during the operation and is deleted immediately after the operation completes with a fail-safe of a few hours. Again there is nothing for the user to delete, Vision API takes care of deleting the data for you.
A related question that sometimes comes up is about enforcing usage to take palce in a particular region. You can see the answer here: Google Vision: How to enforce processing in EU
Depends on your security requirements, and the exact privacy law one needs to abide by. In my case, it was HIPAA, one needs to jump through a lot of hoops, but according to https://cloud.google.com/security/compliance/hipaa, Google Cloud Vision API is a HIPAA covered product.