vania-janet/multiturn-rag-retrieval-data huggingface dataset:
How Is Coronary Microvascular Disease Treated?
If you're diagnosed with coronary MVD and also have anemia, you may benefit from treatment for that condition.
Anemia is thought to slow the growth of cells needed to repair damaged blood vessels.
What causes autoimmune hepatitis?
A combination of autoimmunity, environmental triggers, and a genetic predisposition can lead to autoimmune hepatitis.
What research is being done for Spinal Cord Injury?
The National Institute of Neurological Disorders and Stroke NINDS conducts spinal cord research in its laboratories at the National Institutes of Health NIH.
NINDS also supports additional research through grants to major research institutions across the country.
Some of the more promising rehabilitation techniques are helping spinal cord injury patients become more mobile.
What is Osteogenesis imperfecta OI?
. . .
Show more

Character sequences in words from a custom model are in competition with character sequences from the base model, as well as sequences from other words of the model. (Factors such as audio noise and speaker accents also affect the quality of transcription.)

The accuracy of transcription can depend largely on the data that you add to a model and how speakers say words in audio. To improve the service's accuracy, use corpora to provide as many examples as possible of how words are used in a domain. Repeating the words in corpora can improve the quality of a custom language model. How you duplicate the words in corpora depends on how you expect users to say them in the audio that is to be recognized. The more sentences that you add that represent the context in which speakers use words from the domain, the better the service's recognition accuracy.

For example, accountants adhere to a common set of standards and procedures that are known as Generally Accepted Accounting Principles (GAAP). When you create a custom model for a financial domain, provide sentences that use the term GAAP in context. The sentences help the service distinguish between general phrases such as "the gap between them is small" and domain-centric phrases such as "GAAP provides guidelines for measuring and disclosing financial information."

In general, it is better for corpora to use words in different contexts, which can improve how the service learns the phrases.
"parameters": {
"update_strategy": "merge_once",
"narrowband_recognize": {
"x-watson-learning-opt-out": true,
"grammar_name": "names-abnf",
"language_customization_id": "81d3630-ba58-11e7-aa4b-41bcd3f6f24d"
}
}
}
}
]
}
Show more





 Examples 

The following examples illustrate how to use the speech_to_text response type to send configuration commands to the Speech to Text service.



 Example: Setting the language model 

In this example, the language model is switched to Spanish (es-ES_NarrowbandModel), and smart formatting is enabled.

{
"generic": [
{
"response_type": "speech_to_text",
"command_info": {
"type": "configure",
"parameters": {
"narrowband_recognize": {
"model": "es-ES_NarrowbandModel",
"smart_formatting": true
}
}
}
}
]
}

Show more





 Example: Updating the recognizeBody property for one conversation turn 

The following example shows how to specify the use of a custom language model for a single turn of the conversation turn. This is done by setting update_strategy to merge_once and specifying the the ID of the custom language model in the configuration parameters.

{
"generic": [
{
"response_type": "speech_to_text",
"command_info": {
"type": "configure",
"parameters": {
"update_strategy": "merge_once",
"narrowband_recognize": {
"language_customization_id": "ao45vohgFuxyOQRgztu-02I10ut7aJcM-AdInT-VWgj3V"
}
}
}
"last_scan_date": "24-03-2020 UTC", // the last time the scan was run
"result": "passed"|"failed"], // the result of the scan
"log": {
"url": "https://acme.org/log.txt", // the link to where the actual log of the test is
"hash": "abc123", // the hash of the log file
},
"expired_issues": 134,132,342], // link(s) to the issues for which the grace period expired
"issues": 234,343,342], // link(s) to the issue(s) created to track the bugs found during the test run. Should be populated only if the scan failed
"required": "yes" | "no" ] // yes: this is an auditable step; no: this is a non auditable step
}, {
// Partial CM-4(1) SECURITY IMPACT ANALYSIS | SEPARATE TEST ENVIRONMENTS
// The organization analyzes changes to the information system in a separate test environment before implementation in an operational
// environment, looking for security impacts due to flaws, weaknesses, incompatibility, or intentional malice.
// Partial: RA-5(a) Scans for vulnerabilities in the information system and hosted applications Assignment: organization-defined
// frequency and/or randomly in accordance with organization-defined process] and when new vulnerabilities potentially affecting
// the system/applications are identified and reported;
// Partial: RA-5(b). Employs vulnerability scanning tools and techniques that facilitate interoperability among tools and automate parts
// of the vulnerability management process by using standards for:..
// SA-11 DEVELOPER SECURITY TESTING AND EVALUATION | DYNAMIC CODE ANALYSIS
// The organization requires the developer of the information system, system component, or information system service to employ dynamic code
// analysis tools to identify common flaws and document the results of the analysis.
// Control passed if:
// 1- the script is one of the blessed ones AND
// 2- the status is passed OR
Information system monitoring capability is achieved through a variety of tools and techniques (e.g., intrusion detection systems, intrusion prevention systems, malicious code protection software, scanning tools, audit record monitoring software, network monitoring software). Strategic locations for monitoring devices include, for example, selected perimeter locations and near server farms supporting critical applications, with such devices typically being employed at the managed interfaces associated with controls SC-7 and AC-17. Einstein network monitoring devices from the Department of Homeland Security can also be included as monitoring devices. The granularity of monitoring information collected is based on organizational monitoring objectives and the capability of information systems to support such objectives. Specific types of transactions of interest include, for example, Hyper Text Transfer Protocol (HTTP) traffic that bypasses HTTP proxies. Information system monitoring is an integral part of organizational continuous monitoring and incident response programs. Output from system monitoring serves as input to continuous monitoring and incident response programs. A network connection is any connection with a device that communicates through a network (e.g., local area network, Internet). A remote connection is any connection with a device communicating through an external network (e.g., the Internet). Local, network, and remote connections can be either wired or wireless.
Speech activity detection 

The IBM Watson® Speech to Text service offers two speech activity detection parameters to control what audio is used for speech recognition. The parameters specify the service's sensitivity to non-speech events and to background noise. The parameters are independent: You can use them individually or together.

Speech activity detection is supported for most language models. For more information, see [Language model support](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-inputdetection-support).



 How speech activity detection works 

Speech activity detection consumes the input audio stream and determines which parts of the stream to pass for speech recognition. Speech recognition is adversely affected by background speech and noise, causing the service to transcribe the wrong words, to produce words where none are present, or to omit words that are part of the input audio. The speech activity detection feature can help ensure that only relevant audio is processed for speech recognition.

You can use the feature to control the following aspects of speech recognition:



* Suppress background speech. Call-center data often contains cross-talk ("overhearing") from other agents. You can set a volume threshold below which such background speech is ignored.
* Suppress background noise. Some audio, such as speech recorded in a factory, can contain a high level of background noise. You can set a threshold below which such background noise is ignored.
* Suppress non-speech audio events. Background music and tone events, such as audio played to a client who is waiting on hold on a telephone line, can cause inaccurate recognition. Silence can also result in unnecessary recognition or transcription errors. You can set a threshold below which such events are ignored.



By default, speech activity detection is configured to provide optimal performance for the general case for each model. For specific cases, the default settings might not be optimal and can lead either to slow transcription or to word insertions and deletions. You are encouraged to experiment with different settings to determine which values work best for your audio.





 Speech detector sensitivity 

Use the speech_detector_sensitivity parameter to adjust the sensitivity of speech activity detection.
In addition, you can be alerted on actions as they happen. The events that are collected comply with the Cloud Auditing Data Federation (CADF) standard.

In COS, you can track management and data events.



* By default, these events are not enabled.
* Management events report actions that change the state of resource configurations, bucket properties, and object properties.
* Data events report actions on buckets, objects, and multi-part objects such as creation, deletion, and access.
* You must configure each bucket to enable management events, or management and data events. Notice that you cannot enable data events only for a bucket.



For more information, see [Activity Tracker events](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-at-events).

Enable collection of COS management and data events on the bucket that you use to archive data from a logging instance. Use these events to monitor activity in your COS bucket.

In IBM Cloud® Activity Tracker, you can define views, dashboard, and screens to monitor COS management and data events. You can also configure alerts on views to notify you when a specific condition occurs. On a view, you can configure an email alert, a Slack alert, a PagerDuty alert, or any combination of alerts. For more information, see [Creating custom views](https://cloud.ibm.com/docs/log-analysis?topic=log-analysis-view_logsview_logs_step7) and [Managing alerts](https://cloud.ibm.com/docs/log-analysis?topic=log-analysis-alerts).

For example, you can define a view that reports when an object is archived in a bucket. On that view, you can configure an email alert to notify you when an object has been archived. You might have compliance requirements that require you to control who accesses data that is archived. You can define a view that reports access to a bucket, and define an alert to notify you when that happens.
: You can now enable monitoring of the PostgreSQL datastore to receive updates on its usage and status by the Watson Speech services. The events can be consumed by Prometheus monitoring software or whatever application you use for monitoring. By enabling monitoring for user-defined projects in addition to the default platform monitoring, you can monitor your own projects with the Red Hat® OpenShift® Container Platform monitoring stack. This capability includes an additional property, spec.global.datastores.postgressql.enablePodMonitor, in the Speech services custom resource.

For more information, see the topic Monitoring the PostgreSQL datastore for Watson Speech services in the Administering section of [Watson Speech services on IBM Cloud Pak for Data](https://www.ibm.com/docs/en/cloud-paks/cp-data/4.6.x?topic=services-watson-speech).

Defect fix: PostgreSQL datastore is no longer installed if only runtime microservices are enabled
: Defect fix: The PostgreSQL datastore is no longer installed if only the runtime microservices are enabled. The datastore is now installed only if at least one of the sttAsync, sttCustomization, or ttsCustomization microservices is installed. PostgreSQL is not uninstalled if at a later date these microservices are disabled.

Prior to version 4.6.0, PostgreSQL was always installed with the Speech services. If you are an existing customer who used only the runtime microservices of the Speech services prior to version 4.6.0, PostgreSQL remains installed but is not used. In this case, installation of PostgreSQL persists across upgrades.

The MinIO datastore is always installed because the runtime microservices depend on it. The RabbitMQ datastore is installed only if the sttAsync microservice is installed.
{{site.data.content.newlink}}



 Audit events 

As a security officer, auditor, or manager, you can use the [IBM Cloud Pak for Data audit service](https://www.ibm.com/docs/en/cloud-paks/cp-data/latest?topic=considerations-auditing-cloud-pak-data) to track how users and applications interact with Watson Assistant.

IBM Cloud Pak for Data audit service records user-initiated activities that change the state of a service in Watson Assistant. You can use this service to investigate abnormal activity and critical actions and to comply with regulatory audit requirements. For more information about exporting audit records to your security information and event management (SIEM) solutions, see [Auditing Cloud Pak for Data](https://www.ibm.com/docs/en/cloud-paks/cp-data/latest?topic=considerations-auditing-cloud-pak-data).



 List of events 

The following table lists the Watson Assistant activities that generate events.



Table 1. Activities that generate events

 Action Triggered when someone... 

 conversation.assistant.create creates an assistant. 
 conversation.assistant.delete deletes an assistant. 
 conversation.assistant.update updates an assistant. For example, renames the skill, changes the session timeout, or changes its associated skills. 
 conversation.counterexample.create marks test user input in the Try it out pane as being irrelevant or corrects the categorization of a user input that was incorrectly assigned to an intent by marking it as irrelevant. 
 conversation.counterexample.delete deletes a counterexample. 
 conversation.counterexample.update edits a counterexample. 
 conversation.data.update does a bulk action, such as importing a CSV file of intents or entities to the skill, or deleting multiple training data items, such as multiple entities or intents. 
 conversation.entity.create creates an entity. 
 conversation.entity.delete deletes an entity. 
 conversation.entity.update edits an entity. 
 conversation.example.create adds a user input example to an intent.
AU-13 - Monitoring for Information Disclosure 



  Control requirements 

AU-13 - 0
:   The organization monitors [Assignment: organization-defined open source information and/or information sites] [IBM Assignment: weekly] for evidence of unauthorized disclosure of organizational information.





  NIST supplemental guidance 

Open source information includes, for example, social networking sites.
Logging and monitoring 

Monitoring and logging is part of the service. However, it is not directly displayed to the user. Instead, the infrastructure is used by IBM operational staff to address issues.

You can connect with a Db2 command-line client, such as CLPPlus, to access detailed information and diagnostics.



  A basic overview: 

The following are two basic types of checking your system status:



*  External health and uptime checks
*  Metric-based monitoring



IBM monitors hundreds of metrics and stores those metrics historically. Based on the values of these metrics, alerts are generated. These alerts are sent to IBM operations staff to ensure that the alerts are seen and addressed. In addition, IBM also sends archived operating system and diagnostic logs for rapid diagnosis. Db2 on Cloud complies with GDPR, and IBM EU Cloud options provide an even higher level of adherence to GDPR, if needed.
Monitoring operational metrics 

As a security officer, auditor, or manager, you can use the IBM Cloud Monitoring service to measure how users and applications interact with Hyper Protect Crypto Services.

IBM Cloud Monitoring records data on the operations that occur inside of IBM Cloud. With this service, you can gain operational visibility into the performance and health of your applications, services, and platforms. You can use the advanced features to monitor and troubleshoot, define alerts based on API response codes, and design custom dashboards.

For more information about the Monitoring service, see the [getting started tutorial for IBM Cloud Monitoring](https://cloud.ibm.com/docs/Monitoring-with-Sysdig?topic=Monitoring-with-Sysdig-getting-started-monitor).



 What metrics are available for Hyper Protect Crypto Services? 

You can use Monitoring to track the type of API requests that are made to your Hyper Protect Crypto Services instance as well as the latency of the requests.

The following list contains examples of metrics that can be measured in your Monitoring dashboard:



* Total requests that are made to your Hyper Protect Crypto Services instance.
* Successful and failed API requests categorized by API type.
* API request latency over time.
* Total API requests categorized by response code.







 Before you begin 

Enabling Hyper Protect Crypto Services service metrics add new metrics to your Monitoring instance. For more information about Monitoring pricing, see [Pricing](https://cloud.ibm.com/docs/Monitoring-with-Sysdig?topic=Monitoring-with-Sysdig-pricing_plans).

Before you provision an instance of Monitoring, consider the following guidance:



* You need to enable the [metrics policy](https://cloud.ibm.com/docs/hs-crypto?topic=hs-crypto-manage-monitoring-metrics) for your Hyper Protect Crypto Services instance in order to retrieve operational metrics.
* Other IBM Cloud users with administrator or editor permissions can manage the Monitoring service in the IBM Cloud. These users must also have platform permissions to create resources within the resource group where they plan to provision the instance.







 Connecting Monitoring with Hyper Protect Crypto Services
Frequently Asked Questions 

Frequently asked questions about IBM Cloud Monitoring.



  Where can I find the list of Cloud services that generate metrics? 

You can find information about the services that generate metrics in the following documentation topic: [Cloud services](https://cloud.ibm.com/docs/monitoring?topic=monitoring-cloud_services).





  Are you seeing errors when there are no problems? 

Are you observing monitoring agent connection errors or receiving uptime alerts reporting an host is down when there are no problems?

IBM Cloud Monitoring has identified an issue with a subset of agent versions:



*  monitoring agent 10.3.0
*  monitoring agent 10.3.1
*  monitoring agent 10.4.0
*  monitoring agent 10.4.1



Where connectivity between your infrastructure and Monitoring's hosted service may fail.

You must upgrade all monitoring agents to 10.5. [Learn more](https://cloud.ibm.com/docs/monitoring?topic=monitoring-troubleshoottroubleshoot-entry-3).





  How can I find out the metrics that are collected per agent? 

In IBM Cloud Monitoring, you can monitor your monitoring agent by using the dashboard template monitoring agent Health & Status that is available in Host Infrastructure. In this dashboard, you can see the number of monitoring agents that are deployed and connected to the monitoring instance, check the version of the monitoring agents, and find out how many metrics per host the agent is collecting.
They are logged into Activity Tracker instances. By utilizing Activity Tracker Event Routing, the security records can be centralized to one or few instances with either event search (logdna) or Object Storage as storage options. By aggregating all records in one location, security events can be easily correlated and thereby increasing insights into incidents or even allowing an early detection.





 Log Analysis 

IBM® Log Analysis allows managing operating system logs, application logs, and platform logs and provides search and filtering capabilities. Logs can be streamed from one Log Analysis instance to either [Event Streams](https://cloud.ibm.com/docs/log-analysis?topic=log-analysis-streaming-configure) or [to another Log Analysis instance](https://cloud.ibm.com/docs/log-analysis?topic=log-analysis-streaming-configure-l2l). Thus, by streaming to a central instance, logs can be consolidated for analysis in greater context, thereby improving (security) insights.







 Sharing of network resources 

Designing and developing cloud native apps in an enterprise context often involves coordinating regarding network resources like address ranges and subnets, domain names, and routing of traffic. The different accounts and their applications and compute environments need to fit into the network and its structure. This requires sharing of network resources.

Zoom

![Sharing of network resources](https://cloud.ibm.com/docs-content/v1/content/f84e2238288b7f0355715a4c355609ce7ac48fb0/solution-tutorials/images/solution65-resource-sharing/resource-sharing-architecture-network.svg)

Sharing of network resources



1. The Transit Gateway service is used to interconnect VPC environments and classic infrastructure across the three accounts.
2. Each account has a DNS Services instance to manage private domain names. The instances are connected to share DNS zones.





 DNS Services 

You can use DNS Services to resolve private addresses (domain names) from resources deployed in IBM Cloud. The domain names cannot be resolved from the public internet. A DNS zone is a collection of domain names and consists of DNS resource records.
Activity Tracker events 

IBM Cloud

As a security officer, auditor, or manager, you can use the Activity Tracker service to track how users and applications interact with IBM Watson® Speech to Text in IBM Cloud®.

IBM Cloud Activity Tracker records user-initiated activities that change the state of a service in IBM Cloud. You can use this service to investigate abnormal activity and critical actions and to comply with regulatory audit requirements. In addition, you can be alerted about actions as they happen. The events that are collected comply with the Cloud Auditing Data Federation (CADF) standard. For more information, see the tutorial [Getting started with IBM Cloud Activity Tracker](https://cloud.ibm.com/docs/activity-tracker?topic=activity-tracker-getting-started).



 Language model customization events 

The following tables list the Speech to Text actions for language model customization that generate events.



 Create events 



Table 1. Language model customization .create actions that generate events

 Action Description 

 speech-to-text.custom-language-model.create Create a custom language model (POST /v1/customizations). 
 speech-to-text.custom-language-model-word-list.create Create a word list for a custom language model (POST /v1/customizations/{customization_id}/words). 
 speech-to-text.custom-language-model-word.create Create a word for a custom language model (PUT /v1/customizations/{customization_id}/words/{word_name}). 
 speech-to-text.custom-language-model-corpus.create Create a corpus for a custom language model (POST /v1/customizations/{customization_id}/corpora/{corpus_name}). 
 speech-to-text.custom-language-model-grammar.create Create a grammar for a custom language model (POST /v1/customizations/{customization_id}/grammars/{grammar_name}). 







 Read events 



Table 2. Language model customization .read actions that generate events

 Action Description