vania-janet/multiturn-rag-retrieval-data huggingface dataset:
For more information about publishing, see [Publishing your content](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-publish).





 Environment settings 

The draft and live environments each have settings. On either tab, click the Settings gear icon to open the settings.

API details provide these values for each environment:



* Environment name
* Environment ID
* Session URL



Webhooks

Settings for pre-message, post-message, and log webhooks. For more information, see [Extending your assistant with webhooks](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-webhook-overview).

Inactivity timeout

Specify the amount of time to wait after the customer stops interacting with the assistant before ending the session.

When a customer connects to your assistant through one of the built-in integrations, or through a custom client that uses the stateful message API, the session ends after the specified timeout interval.

When the session ends, the assistant loses any contextual information that it saved during the conversation with the customer. For example, if the assistant asks for the customer's name and then calls the customer by that name throughout the rest of the conversation, then after the session ends and a new one begins, the assistant will start by asking for the customer's name again.

The maximum inactivity timeout differs by service instance plan type. The following table lists the limits.



Service plan details

 Service plan Chat session default inactivity period Chat session maximum inactivity period 

 Enterprise 1 hour 168 hours (7 days) 
 Premium (legacy) 1 hour 168 hours (7 days) 
 Plus 1 hour 24 hours 
 Trial 5 minutes 5 minutes 
 Lite 5 minutes 5 minutes
Certain objects might need to be prevented from modification after a retention period expires. An example is an incomplete legal review, where records might need to be accessible for an extended duration beyond the retention period originally set. A legal hold flag can then be applied at the object level. Legal holds can be applied to objects during initial uploads or after an object is written. Note: A maximum of 100 legal holds can be applied per object.





 Indefinite retention 

Allows the user to set the object to be stored indefinitely until a new retention period is applied. This is set at a per object level.





 Event-based retention 

Immutable Object Storage allows users to set indefinite retention on the object if they are unsure of the final duration of the retention period, or want to use event-based retention. Once set to indefinite, user applications can then can change the object retention to a finite value later. For example, a company has a policy of retaining employee records for three years after the employee leaves the company. When an employee joins the company, the records that are associated with that employee can be indefinitely retained. When the employee leaves the company, the indefinite retention is converted to a finite value of three years from the current time, as defined by company policy. The object is then protected for three years after the retention period change. A user or third-party application can change the retention period from indefinite to finite retention that uses an SDK or REST API.





 Permanent retention 

Permanent retention ensures that data can not be deleted, ever, by anyone. Read the documentation carefully and do not use permanent retention unless there is a compelling regulatory or compliance need for permanent data storage.

Permanent retention can only be enabled at a IBM Cloud Object Storage bucket level with retention policy enabled and users are able to select the permanent retention period option during object uploads. Once enabled, this process can't be reversed and objects uploaded that use a permanent retention period cannot be deleted. It's the responsibility of the users to validate at their end if there's a legitimate need to permanently store objects by using Object Storage buckets with a retention policy.
Event retention By default, the event retention is set to 30 days. You need to change this setting in the VMware vSphere Web Client. Click the Configure tab, Settings, and General. Click Edit, change the Event Retention to the required number of days, and click OK. 
 View Triggered Alarms To view the triggered alarms, navigate to vCenter and select either All or New in the Alarms pane. This list refreshes every 120 seconds. To view alarms triggered on a selected inventory object, select the object. Click the Monitor tab, Issues, and select Triggered Alarms. 







 Related links 



* [vSphere monitoring and performance](https://docs.vmware.com/en/VMware-vSphere/6.7/vsphere-esxi-vcenter-server-67-monitoring-performance-guide.pdf)
Identify the table for which you want to view the retention interval.

The retention interval is displayed in the Retention time interval (days) column.





* For a schema:





1. Go to Databases.
2. Select the database in which the schema that you want to view the retention interval is located.
3. Identify the schema for which you want to view the retention interval.

The retention interval is displayed in the Retention time interval (days) column.





* For a database:





1. Go to Databases.
2. Identify the database for which you want to view the retention interval.

The retention interval is displayed in the Retention time interval (days) column.
* [Word timestamps](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metadataword-timestamps) return timestamps for the start and end of each word of a transcript.







 Processing and audio metrics 



* [Processing metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metricsprocessing-metrics) provide detailed timing information about the service's analysis of the input audio. The service returns the metrics at specified intervals and with transcription events, such as interim and final results. You can use the metrics to gauge the service's progress in transcribing the audio. You can request processing metrics with the WebSocket and asynchronous HTTP interfaces.
* [Audio metrics](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-metricsaudio-metrics) provide detailed information about the signal characteristics of the input audio. The results provide aggregated metrics for the entire input audio at the conclusion of speech processing. You can use the metrics to determine the characteristics and quality of the audio. You can request audio metrics with any of the service's interfaces.









 Customizing the service 

The customization interface lets you create custom models to improve the service's speech recognition capabilities:



* [Custom language models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate) let you define domain-specific words for a base model. Custom language models can expand the service's base vocabulary with terminology specific to domains such as medicine and law. Language model customization is available for both previous- and next-generation models, though it works differently for the two types of models.
* [Custom acoustic models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acoustic) let you adapt a base model for the acoustic characteristics of your environment and speakers. Custom acoustic models improve the service's ability to recognize speech with distinctive acoustic characteristics.
Retention policies ensure that data is stored in a Write-One-Read-Many (WORM), non-erasable, and non-rewritable manner. You cannot change or delete objects in protected buckets within the retention period, or delete protected buckets with objects themselves until the retention period is over. The policy is enforced until the end of a retention period and the removal of any legal holds.

It is recommended that teams set a retention policy for the buckets that are used as their evidence locker that stores every object for a minimum of 365 days.







 Audit event log 

For buckets that are not configured, access log data is available for Immutable Object Storage through support requests.

With [IBM Cloud Activity Tracker](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-at), you can [audit the requests](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-at-events) that are made against a bucket and the objects it contains. You can review all of the Object Storage events that are related to the evidence locker bucket on the IBM Cloud Activity Tracker web UI. You can also have all of the data that is collected in an instance of IBM Cloud Activity Tracker archived and written to a separate bucket.





 Bucket access permissions 

Pipelines put objects (evidence, evidence summary, and artifacts) and read objects (evidence summary) from Buckets. The tools do not alter or delete objects or create, update, or delete Buckets.

Use the following access policies to access the Cloud Object Storage buckets:



* Reader. Required for the CD pipeline to check the bucket retention policy.
* Object Writer. Required for all CI, CD, and CC pipelines to persist new evidence into buckets.



When you use the Cloud Object Storage bucket as the evidence storage, the recommended permissions are Reader and Object writer. Permissions that have higher privileges might be harmful.





 Storage classes 

Costs vary for teams with different setups and deployment frequency. It is not recommended that you use the free tier as Cloud Object Storage buckets because the free tier cannot be configured to be immutable.



 Sample estimation
* For more information about using the WebSocket interface to obtain word timings, see [Generating word timings](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-timing).
* For more information about customization, see [Understanding customization](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-customIntro).
* For more information about the use of IPA and SPR with customization, see [Understanding phonetic symbols](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-symbols). (The IPA symbols for the Arabic, Chinese, Netherlands Dutch, and Korean languages are not yet documented. This documentation will be made available soon.)







 24 February 2020 

New US English and German neural voices
: The service now supports five new neural voices:



* US English: en-US_EmilyV3Voice, en-US_HenryV3Voice, en-US_KevinV3Voice, and en-US_OliviaV3Voice
* German: de-DE_ErikaV3Voice



The new voices do not support the following SSML elements:



* Expressive SSML with the <express-as> element
* Voice Transformation with the <voice-transformation> element
* The volume attribute of the <prosody> element



For more information about these and all available voices, see [Languages and voices](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-voices).

New support for Activity Tracker
: The service now supports the use of Activity Tracker events for all customization operations. 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.
There is no default retention period applied. You can set it while creating the bucket.





 Can we add a retention policy to an existing bucket? 

Yes, [Retention policies](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-immutableimmutable-sdk-add-policy) can be added to an existing bucket; however, the retention period can only be extended. It cannot be decreased from the currently configured value.





 Why is there a "legal hold" concept on top of the "retention period"? 

A legal hold prevents an object from being overwritten or deleted. However, a legal hold does not have to be associated with a retention period and remains in effect until the legal hold is removed. For details, see [Legal hold and retention period](https://cloud.ibm.com/docs/cloud-object-storage?topic=cloud-object-storage-immutableimmutable-terminology-hold).





 How can I access a private COS endpoint in a data center from another date center? 

Use Object Storage [Direct Link Connection](https://cloud.ibm.com/docs/direct-link?topic=direct-link-using-ibm-cloud-direct-link-to-connect-to-ibm-cloud-object-storage) to create a global direct link.





 How does frequency of data access impact the pricing of Object Storage? 

Storage cost for Object Storage is determined by the total volume of data stored, the amount of public outbound bandwidth used, and the total number of operational requests processed by the system. For details, see [cloud-object-storage-billing](https://cloud.ibm.com/docs/cloud-object-storage/iam?topic=cloud-object-storage-billing).





 What are the considerations for choosing the correct storage class in Object Storage? 

You can choose the correct storage class based on your requirement. For details, see [billing-storage-classes](https://cloud.ibm.com/docs/cloud-object-storage/iam?topic=cloud-object-storage-billingbilling-storage-classes).
Extract each individual channel from the audio.
2. Transcribe the audio from each channel separately and without using the speaker_labels parameter. Include the timestamps parameter to learn precise timing information for the words of the transcripts.
3. Merge the results of the individual requests to re-create a single transcript of the complete exchange. You can use the timestamps of the individual requests to reconstruct the conversation.



The multichannel approach has some advantages over the use of the speaker_labels parameter:



* Because it relies on basic speech recognition, the service can transcribe audio that is in any supported language. Speakers labels are restricted to a subset of the available languages.
* Because each speaker has a dedicated channel, the service can provide more accurate results than it can for speaker labels. The service does not need to determine which speaker is talking.
* Because each speaker has a dedicated channel, the service can accurately transcribe cross-talk, or speaker overlap. On a merged channel, cross-talk can be difficult or impossible to recognize accurately.



But the approach also has some disadvantages that you need to be aware of:



* You must separate the channels prior to sending the audio and then merge the resulting transcripts to reconstruct the conversation. The use of timestamps greatly simplifies the reconstruction process.
IBM Cloud

You are charged for all audio that you send to the service, including silence. If you send the audio from all channels in its entirety, you effectively multiply the amount of audio being recognized by the number of channels. For example, if you submit separate requests for both channels of a two-channel exchange that lasts for five minutes, your requests require ten minutes of audio processing. If your pricing plan uses per-minute pricing, this doubles the cost of speech recognition. You can consider preprocessing the audio to eliminate silence, but that approach makes it much more difficult to merge the results of the separate requests.
The object for each match includes the following fields:



* normalized_text is the specified keyword that is normalized to the spoken phrase that matched in the input audio.
* start_time is the start time in seconds of the match.
* end_time is the end time in seconds of the match.
* confidence is the service's confidence that the match represents the specified keyword. The confidence must be at least as great as the specified threshold to be included in the results.



A keyword for which the service finds no matches is omitted from the array. A keyword might not be found if



* The audio simply does not include the keyword. Absence of the keyword is the most obvious explanation.
* The threshold is set too high. The service might identify the keyword but with a lower level of confidence, in which case it omits the match from the results.
* A keyword string that contains multiple tokens (for example, Speech to Text) is spoken with too much silence between its tokens. When the service transcribes audio, it chops the stream into a series of blocks. Each block represents a continuous chunk of audio that does not have an interval of silence that exceeds half of a second. It constructs an array of result objects that consists of these blocks.

The service matches a multi-token keyword only if



* The keyword's tokens are in the same block.
* The tokens are either adjacent or separated by a gap of no more than 0.1 seconds.



In the latter case, a brief filler or non-lexical utterance, such as "uhm" or "well," can lie between two tokens of the keyword. In this case, previous-generation models can insert a hesitation marker at this position of the transcript. Next-generation models include the actual hesitation in the transcription results. For more information, see [Speech hesitations and hesitation markers](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-basic-responseresponse-hesitation).







 Keyword spotting example
By default, the service transcribes an entire audio stream as a single utterance and returns a single final result for all of the audio. However, the service can return multiple final results in response to the following conditions:



* The audio contains a pause or extended silence between spoken words or phrases. For most languages, the default pause interval that the service uses to determine separate final results is 0.8 seconds. For Chinese, the default interval is 0.6 seconds. You can use the end_of_phrase_silence_time parameter to change the duration of the pause interval. For more information, see [End of phrase silence time](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-parsingsilence-time).
* For previous-generation models, the utterance reaches a two-minute maximum. The service splits a transcript into multiple final results after two minutes of continuous processing.



The following examples show responses with two final results from the HTTP and WebSocket interfaces. The same input audio is used in both cases. The audio speaks the phrase "one two three four five six," with a one-second pause between the words "three" and "four." The examples use the default pause interval for speech recognition.



* For the HTTP interfaces, the service always sends a single SpeechRecognitionResults object. The alternatives array has a separate element for each final result. The response has a single result_index field with a value of 0.

{
"result_index": 0,
"results": [
{
"alternatives":
{
"confidence": 0.99,
"transcript": "one two three "
}
],
"final": true
},
{
"alternatives":
{
"confidence": 0.99,
"transcript": "four five six "
}
],
"final": true
}
]
}
Show more
* For the WebSocket interface, the service sends the same results as the previous example.
For more information, see [Speech hesitations and hesitation markers](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-basic-responseresponse-hesitation).





 4 June 2020 

Defect fix: Improve latency for custom language models with many grammars
: Defect fix: The latency issue for custom language models that contain a large number of grammars has been resolved. When initially used for speech recognition, such custom models could take multiple seconds to load. The custom models now load much faster, greatly reducing latency when they are used for recognition.





 28 April 2020 

Updates to Italian models for improved speech recognition
: The Italian broadband (it-IT_BroadbandModel) and narrowband (it-IT_NarrowbandModel) models have been updated for improved speech recognition. By default, the service automatically uses the updated models for all speech recognition requests. If you have custom language or custom acoustic models that are based on these models, you must upgrade your existing custom models to take advantage of the updates by using the following methods:



* POST /v1/customizations/{customization_id}/upgrade_model
* POST /v1/acoustic_customizations/{customization_id}/upgrade_model



For more information, see [Upgrading custom models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade).

Dutch and Italian models now generally available
: The Dutch and Italian language models are now generally available (GA) for speech recognition and for language model and acoustic model customization:



* Dutch broadband model (nl-NL_BroadbandModel)
* Dutch narrowband model (nl-NL_NarrowbandModel)
* Italian broadband model (it-IT_BroadbandModel)
* Italian narrowband model (it-IT_NarrowbandModel)



For more information about all available language models, see



* [Supported previous-generation language models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-modelsmodels-supported)
After it is restored, you must upgrade your plan within 1 hour or it will be deleted again.

The Secrets Manager data retention policy describes how long your data is stored after you delete the service. The data retention policy is included in the Secrets Manager service description, which you can find in the [IBM Cloud Terms and Notices](https://cloud.ibm.com/docs/overview?topic=overview-terms).



 Deleting a Secrets Manager instance 

If you no longer need an instance of Secrets Manager, you can delete the service instance and any data that is stored. Your instance enters a disabled state, and after 7 days its data is permanently deleted. You can also choose to delete your service instance by using the console.

During the 7-day reclamation period, do not delete authorizations between Secrets Manager and other integrated services, such as Key Protect. Secrets Manager uses the authorization to unregister your instance from any associated resources in those services. After the instance is permanently deleted, the authorization is also deleted by IAM.



1. Delete the service and place it in a reclamation period of 7 days.

ibmcloud resource service-instance-delete "<instance_name>"

Replace <instance_name> with the name of the Secrets Manager instance that you want to delete.
2. Optional: To permanently delete your instance, get the reclamation ID.

ibmcloud resource reclamations --resource-instance-id <instance_ID>

Replace <instance_ID> with your Secrets Manager instance ID.

If you choose to permanently delete the instance by deleting its reclamation, you cannot restore your data.
3. Optional: Permanently delete the reclamation instance.

ibmcloud resource reclamation-delete <reclamation_ID>

Replace <reclamation_ID> with the value that you retrieved in the previous step.







 Restoring a deleted service instance 

If you haven't permanently deleted your instance, you can restore it during the 7-day reclamation period.



1. View which service instances are available for restoration.

ibmcloud resource reclamations

From the list of available instances, copy the reclamation ID of the Secrets Manager instance that you want to restore.
2.