ibm-cloud

I understand that Watson Speech To Text is somewhat calibrated for colloquial conversation and for 1 or 2 speakers. I also know that it can deal with FLAC better than WAV and OGG. I would like to know how could I improve the algorithm recognition, acoustically speaking. I mean, does increasing volume help? Maybe using some compression filter? Noise reduction? What kind of pre processing could help for this service? the best way to improve the accuracy of the base models (which are very accurate but also very general) is by using the Watson STT customization service: https://www.ibm.com/watson

After testing the discovery service , it seems useless to me at least or I might be missing something. When I query, it matches the document and returns the whole document . If my document is huge, then for all queries it returns the whole document matching the query text, which is useless. Now Do I have to create a separate document for every query? If that's the case, API.AI or WIT.AI is a better option. Please clear me on what I am missing in here! For now with Discovery, you would need to break up your documents once to put them in a collection, then any query against the collection in

I am using the Business Rules service on Bluemix, and it does not seem to use the Decision Warehouse. Is there another way to trace the rule firing? As you noticed, the Decision Warehouse is not a feature within the Business Rules service. Also, rule traces are disabled. You can add trace filter tags to the payload request. Use the REST form ( &trace=true ) to view the trace filter tags: https://brsv2- instanceID . domain /DecisionService/run.jsp?path=/ ruleApp /1.0/ ruleset /1.0&trace=true (You can get the values for instanceID , domain , ruleApp , ruleset and the corresponding versions from

I have a Spark application that I am submitting to the Bluemix Spark Cluster. It reads from a DASHDB database and writes the results to Cloudant. The code accesses the DASHDB using both Spark and JDBC. The userid & password for the DASHDB database are passed as arguments to the program. I can pass these parameters via spark-submit but I don't think that would be secure. In the code I need to know the credentials of the DASHDB database because I am using JDBC to connect to various tables. I am trying to find the "Best Practices" way to pass credentials using spark-submit in a secure manner.

I am developing an application which the frontend is an AngularJS API that makes requests to the backend API developed in Django Rest Framework. The frontend is on the domain: https://front.bluemix.net And my backend is on the domain: https://back.bluemix.net I am having problems making requests from the frontend API to the backend API. The error is this: Error: CSRF Failed: Referer checking failed - https://front.bluemix.net does not match any trusted origins. I am using CORS and I have already included the following lines in my settings.py in the Django backend API: ALLOWED_HOSTS = [] CORS

I have an existing WebSphere Application Server v7 application and I would like to run it on the Liberty runtime in Bluemix. Can I simply take the app as-is and try importing it into one of the starter apps I see in Bluemix? The short answer, yes, you can take your existing WebSphere Application Server v7 application, create a Java Cache Web starter application and download the starter code, modify the code with your existing application, bind any appropriate services and push the application to Bluemix. However, there may be Java EE programming model and WebSphere API differences between

How do I add a certificate to the trust store when application is running in bluemix. Is there any way to update cacert, either programmatically or using cli? Any documentation or link on the same will be greatly appreciated. Jack-Junjie Cai You can push a packaged server to the Liberty buildpack. With the packaged server, you can package the cert and configure the server.xml accordingly (see https://www-01.ibm.com/support/knowledgecenter/was_beta_liberty/com.ibm.websphere.wlp.nd.multiplatform.doc/ae/rwlp_sec_keystores.html ). The server.xml will be part of the packaged server. If you need to

I have a DSX notebook that I can run manually usng the DSX user interface and it populates some data in a Cloudant database. I have scheduled the notebook to run hourly. Overnight I would have expected the job to have run many times, but the Cloudant database has not been updated. How can I debug the scheduled job? Are there any logs that I can check to verify that the notebook has actually been executed? Is the output from my notebook saved to log files? Where can I find these files? One possibility is to look into the kernel logs of your notebook kernel. For that you need to use a Python