vania-janet/multiturn-rag-retrieval-data huggingface dataset:
For more information about the effects of custom model upgrading on speech recognition with both types of custom models, see [Considerations for using custom acoustic and custom language models together](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-upgrade-usecustom-upgrade-use-recognition-both).



 Example of using both custom language and custom acoustic models 

The following example request passes both custom acoustic and custom language models to the HTTP POST /v1/recognize method:

IBM Cloud

curl -X POST -u "apikey:{apikey}" --header "Content-Type: audio/flac" --data-binary @audio-file1.flac "{url}/v1/recognize?acoustic_customization_id={customization_id}&language_customization_id={customization_id}"

IBM Cloud Pak for Data

curl -X POST --header "Authorization: Bearer {token}" --header "Content-Type: audio/flac" --data-binary @audio-file1.flac "{url}/v1/recognize?acoustic_customization_id={customization_id}&language_customization_id={customization_id}"

For an asynchronous HTTP request, you specify the parameters when you create the asynchronous job. For a WebSocket request, you pass the parameters when you establish a connection. For more information, see [Using a custom language model for speech recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageUse) and [Using a custom acoustic model for speech recognition](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acousticUse).
For information about all methods of the interface, see the [API & SDK reference](https://cloud.ibm.com/apidocs/speech-to-text).

New numeric redaction feature for US English, Japanese, and Korean now available
: A new numeric redaction feature is now available to mask numbers that have three or more consecutive digits. Redaction is intended to remove sensitive personal information, such as credit card numbers, from transcripts. You enable the feature by setting the redaction parameter to true on a recognition request. The feature is beta functionality that is available for US English, Japanese, and Korean only. For more information, see [Numeric redaction](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-formattingnumeric-redaction).

New French and German narrowband models now available
: The following new German and French language models are now available with the service:



* French narrowband model (fr-FR_NarrowbandModel)
* German narrowband model (de-DE_NarrowbandModel)



Both new models support language model customization (GA) and acoustic model customization (beta). For more information, see [Language support for customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support).

New US English en-US_ShortForm_NarrowbandModel now available
: A new US English language model, en-US_ShortForm_NarrowbandModel, is now available. The new model is intended for use in Interactive Voice Response and Automated Customer Support solutions. The model supports language model customization (GA) and acoustic model customization (beta). For more information, see [The US English short-form model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-modelsmodelsShortform).

Updates to UK English and Spanish narrowband models for improved speech recognition
: The following language models have been updated for improved speech recognition:
Metrics with graphical views 

Metrics for an individual CDN are provided on the Overview tab of the customer portal for that CDN mapping. Two types of metrics are calculated from the CDN's usage: those that show the metrics over a time period as a graph, and those that are shown as aggregate values.

For metrics that display the change over a period of time as a graph, you can see three line graphs and a pie chart. The three line graphs are: Bandwidth, Hits by Mapping, and Hits by Type. They display the activity daily over the course of your specified timeframe. The graphs for Bandwidth and Hits by Mapping are single-line graphs, whereas the breakdown of Hits by Type shows a line for each of the hit types provided. The pie chart displays a regional breakdown of the bandwidth for a CDN mapping on a percentage basis.

Metrics that are shown for aggregate values include Bandwidth Usage in GB, Total Hits to the CDN Edge server, and the Hit Ratio. Hit Ratio indicates that the percentage of times content is delivered by the Edge server, not through its origin. Hit ratio currently is shown as a function of all your CDN mappings, not just the one being viewed.

By default, both the aggregate numbers and the graphs default to show metrics for the last 30 days, but you can change this through the [IBM Cloud console](https://cloud.ibm.com/). Both categories can display metrics for 7-, 15-, 30-, 60-, or 90-day periods.





 Object storage origin support 

IBM Cloud CDN can be configured to serve content from an object storage endpoint by providing the endpoint, the bucket name, protocol, and port. Optionally, you can specify a list of file extensions to allow caching for files only with those extensions. All objects in the bucket must be set with anonymous read or public read access.

For more information, see [Accelerate delivery of static files using a CDN](https://cloud.ibm.com/docs/solution-tutorials?topic=solution-tutorials-static-files-cdn).





 Path-based CDN mappings
TS_CROSS_CORRELATION(DoubleTimeSeries, DoubleTimeSeries)
: Output: DoubleArray
: Use a [cross correlation](https://en.wikipedia.org/wiki/Cross-correlation) algorithm to return a measure of the similarity of two time series.

TS_SEG_CROSS_CORRELATION(DoubleSegmentTimeSeries, DoubleSegmentTimeSeries)
: Output: DoubleArrayTimeSeries
: Use a [cross correlation](https://en.wikipedia.org/wiki/Cross-correlation) algorithm to return a measure of the similarity of each pair of corresponding segments in the two input time series. Each timetick in the output time series is the timetick of the corresponding segment.

TS_AVG(DoubleTimeSeries)
: Output: Double
: Returns the average of the values of the input time series.

TS_SEG_AVG(DoubleSegmentTimeSeries)
: Output: DoubleTimeSeries
: Returns the average of the values of each segment of the input time series. Each timetick in the output time series is the timetick of the corresponding segment.

TS_MIN(DoubleTimeSeries)
: Output: Double
: Returns the minimum value of the input time series.

TS_SEG_MIN(DoubleSegmentTimeSeries)
: Output: DoubleTimeSeries
: Returns the minimum value of each segment of the input time series. Each timetick in the output time series is the timetick of the corresponding segment.

TS_MAX(DoubleTimeSeries)
: Output: Double
: Returns the maximum value of the input time series.

TS_SEG_MAX(DoubleSegmentTimeSeries)
: Output: DoubleTimeSeries
: Returns the maximum value of each segment of the input time series. Each timetick in the output time series is the timetick of the corresponding segment.

TS_SUM(DoubleTimeSeries)
: Output: Double
: Returns the sum of the values of the input time series.

TS_SEG_SUM(DoubleSegmentTimeSeries)
: Output: DoubleTimeSeries
Three tunnels are created between the tunnel server and the connector to support redundancy across the three availability zones of your location.



Metadata for the location tunnel numbers metric

 Metadata Description 

 Metric Name ibm_satellite_link_location_tunnel_count 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name, Location ID 







 Location latency 

The total round trip time of data in milliseconds for the location.



Metadata for the location latency metric

 Metadata Description 

 Metric Name ibm_satellite_link_location_rtt_second 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name, Location ID 







 Location traffic to cloud 

The total rate of data in bytes per second in the to-cloud direction for the location.



Metadata for the location traffic to cloud metric

 Metadata Description 

 Metric Name ibm_satellite_link_location_to_cloud_data_rate 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name, Location ID 







 Location traffic from cloud 

The total rate of data in bytes per second in the from-cloud direction for the location.



Metadata for the location traffic from cloud metric

 Metadata Description 

 Metric Name ibm_satellite_link_location_from_cloud_data_rate 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name, Location ID 







 Location traffic total 

The total rate of data in bytes per second in to-cloud and from-cloud directions for the location.



Metadata for the location traffic total metric

 Metadata Description 

 Metric Name ibm_satellite_link_location_total_data_rate 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name, Location ID 







 Endpoint connection count 

The total number of connections present at the endpoint.



Metadata for the Endpoint connection count metric

 Metadata Description 

 Metric Name ibm_satellite_link_endpoint_connection_count 
 Metric Type gauge 
 Value Type none 
 Segment By Service instance, Service instance name, Location ID, Endpoint ID, Endpoint Name 







 Endpoint traffic to cloud 

The rate of data in bytes per second in the to-cloud direction for the endpoint.
Returns the integrated metrics data for the given mapping, which includes the total number of predetermined statistics, detailed hits and bandwidth, hits by type, and the bandwidth by region. The value of frequency is day by default. For more details, see [View the examples](https://cloud.ibm.com/docs/CDN?topic=CDN-code-examples-using-the-cdn-apiexample-code-for-getting-integrated-metrics).



* Parameters:



* mappingUniqueId - Provide a unique ID of the mapping for which metrics are queried.
* startTime - Provide the start date timestamp (UTC+0) for query.
* endTime - Provide the end date timestamp (UTC+0) for query.
* frequency - Provide the data frequency for data format. The following options are available to configure frequency:



* aggregate - Aggregated metrics data from startDate to endDate.
* day - Daily metrics data from startDate to endDatedefault.





* Return - A collection of objects of type SoftLayer_Container_Network_CdnMarketplace_Metrics.



--------------------





 getMappingUsageMetrics 

Returns the total number of predetermined statistics for direct display for the given mapping. The value of frequency is aggregate by default.



* Parameters:



* mappingUniqueId - Provide a unique ID of the mapping for which metrics are queried.
* startDate - Provide the start date timestamp (UTC+0) for query.
* endDate - Provide the end date timestamp (UTC+0) for query.
* frequency - Provide the data frequency for data format, the following options are available to configure frequency:



* aggregate - Aggregated metrics data from startDate to endDatedefault.
* day - Daily metrics data from startDate to endDate.





* Return - A collection of objects of type SoftLayer_Container_Network_CdnMarketplace_Metrics.
* Metric name - Name of the collected metric.
* Metric type - Determines whether the metric value is a counter metric or a gauge metric. Each of these metrics is of the gauge type, which represents a single numerical value that can arbitrarily fluctuate over time.
* Value type - A unit of measurement for a specific metric. Examples include bytes or counts. A value type of none means that the metric value represents individual occurrences of that metric type.
* Segment - How you want IBM Cloud Monitoring to divide and display the monitoring metrics.







 VPN server metric definitions 

The following tables define the basic VPN server metrics on IBM Cloud for VPC.



 VPN server data bytes input 

Bytes received per minute for a VPN server



Table 1: VPN server data bytes input

 Metadata Description 

 Metric name ibm_is_vpn_server_data_received_bytes 
 Metric type gauge 
 Value type byte 
 Segment by Service instance, Service instance name, VPN server name 







 VPN server data bytes output 

Bytes sent per minute for a VPN server



Table 2: VPN server data bytes output

 Metadata Description 

 Metric name ibm_is_vpn_server_data_sent_bytes 
 Metric type gauge 
 Value type byte 
 Segment by Service instance, Service instance name, VPN server name 







 VPN server CRL days until expiration 

Days until the expiration of the Certificate Revocation List (CRL) for a VPN server



Table 3: VPN server CRL days until expiration

 Metadata Description 

 Metric name ibm_is_vpn_server_crl_days_expiry 
 Metric type gauge 
 Value type none 
 Segment by Service instance, Service instance name, VPN server name 







 VPN server authentication failure count 

Number of authentication failures for a VPN server



Table 4: VPN server authentication failure count

 Metadata Description 

 Metric name ibm_is_vpn_server_authentication_failure_count 
 Metric type gauge 
 Value type none 
 Segment by Service instance, Service instance name, VPN server name 







 VPN server active client count 

Number of active clients for a VPN server



Table 5: VPN server active client count
* With the HTTP interfaces, you specify a query parameter with a speech recognition request.



The service returns audio metrics with the final transcription results. It returns the metrics just once for the entire audio stream. Even if the service returns multiple transcription results (for different blocks of audio), it returns only a single instance of the metrics at the very end of the results.

The WebSocket interface accepts multiple audio streams (or files) with a single connection. You delimit different streams by sending stop messages or empty binary blobs to the service. In this case, the service returns separate metrics for each delimited audio stream.





 Understanding audio metrics 

The service return the metrics in the audio_metrics field of the SpeechRecognitionResults object.

{
"results": [
. . .
],
"result_index": integer,
"audio_metrics": {
"sampling_interval": float,
"accumulated": {
"final": boolean,
"end_time": float,
"signal_to_noise_ratio": float,
"speech_ratio": float,
"high_frequency_loss": float,
"direct_current_offset": [
{"begin": float, "end": float, "count": integer},
. . .
],
"clipping_rate": [
{"begin": float, "end": float, "count": integer},
. . .
],
"speech_level": [
{"begin": float, "end": float, "count": integer},
. . .
],
"non_speech_level": [
{"begin": float, "end": float, "count": integer},
. . .
]
}
}
}
Show more

The audio_metrics field includes an AudioMetrics object that has two fields:
To setup a metric, complete the follow steps.



1. Click Alerts on the side menu.
2. Click Add Alert at the top of the page.
3. Select Metric as the alert type.
4. Select the aggregation and the metric that you would like to be performed on.
5. Select the scope if applicable.
6. Set the metric and time requirements for the alert to trigger.
7. Configure and set up the notification channel and notification interval.
8. Click the CREATE button.



The figure as shown provides an example of how to configure an alert when your service instance receives multiple 401 and 403 errors within a 10 minute time span.

Zoom

![An example of a 401 and 403 configuration.](https://cloud.ibm.com/docs-content/v1/content/0bc8db34a3d90b2a5103c9c71b08a96de9525bbc/key-protect/images/monitor-401-alert.png)

Figure 5. The configuration for a 401 alert in a Monitoring dashboard.
You can define a metric alert directly from the Alerts section.

Complete the following steps to define an alert on a metric:



1. [Launch the monitoring UI](https://cloud.ibm.com/docs/monitoring?topic=monitoring-launch).
2. Verify that you have a notification channel that defines how you want to be notified.

You can enabled 1 or more notification channels when you configure an alert. If you need multiple notification channels, check they are available.
3. Navigate to the Alerts section ![Alerts module](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/images/alerts.png)) in the Web UI.
4. Select Add Alert.

Zoom

![Add alert](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/platform/images/sysdig-platform-7.png)

Add alert
5. Select your desired alert type.

Zoom

![Choose alert type](https://cloud.ibm.com/docs-content/v1/content/220cdcbf6f4421bd7fee83fd1028048dba3f16c8/monitoring/platform/images/sysdig-platform-16.png)

Choose alert type
6. Configure the alert. Set the following fields:

Name: Enter a name for the alert.

Description: Add a description that other users can read to get more context. This field is optional.

Group: The alert group this alert will be part of. If not specified, the alert will be part of the default group.

Severity: Set the level of criticality of the alert. Valid values are High, Medium, Low, and Info.
The metrics indicate the progress and complexity of the engine's processing:



* seen_by_engine is audio that the service has read and passed to the engine at least once.
* received - seen_by_engine is audio that has been buffered at the service but has not yet been seen or processed by the engine.
* The relationship between the times is received >= seen_by_engine >= transcription >= speaker_labels.



The following relationships can also be helpful in understanding the results:



* The values of the received and seen_by_engine fields are greater than the values of the transcription and speaker_labels fields during speech recognition processing. The service must receive the audio before it can begin to process results.
* The values of the received and seen_by_engine fields are identical when the service has finished processing the audio. The final values of the fields can be greater than the values of the transcription and speaker_labels fields by a fractional number of seconds.
* The value of the speaker_labels field typically trails the value of the transcription field during speech recognition processing. The values of the transcription and speaker_labels fields are identical when the service has finished processing the audio.







 Processing metrics example: WebSocket interface 

The following example shows the start message that is passed for a request to the WebSocket interface. The request enables processing metrics and sets the processing metrics interval to 0.25 seconds. It also sets the interim_results and speaker_labels parameters to true. The audio contains the simple message "hello world long pause stop."

function onOpen(evt) {
var message = {
action: 'start',
content-type: 'audio/flac',
processing_metrics: true,
processing_metrics_interval: 0.25,
interim_results: true,
speaker_labels: true
};
websocket.send(JSON.stringify(message));
websocket.send(blob);
}

The following example output shows the first few processing metrics results that the service returns for the request.

{
"processing_metrics": {
"processed_audio": {
--------------------





 getMappingHitsByTypeMetrics 

Returns the total number of hits at a certain frequency over a given range of time. Frequency can be day, week, and month, where each interval is one plot point for a graph. Return data must be ordered based on startDate, endDate, and frequency. The value of frequency is aggregate by default.



* Parameters:



* mappingUniqueId - Provide a unique ID of the mapping for which metrics are queried.
* startDate - Provide the start date timestamp (UTC+0) for query.
* endDate - Provide the end date timestamp (UTC+0) for query.
* frequency - Provide the data frequency for data format, the following options are available to configure frequency:



* aggregate - Aggregated metrics data from startDate to endDatedefault.
* day - Daily metrics data from startDate to endDate.
* week - Weekly metrics data from startDate to endDate.
* month - Monthly metrics data from startDate to endDate.





* Return - A collection of objects of type SoftLayer_Container_Network_CdnMarketplace_Metrics.



--------------------





 getMappingBandwidthMetrics 

Returns the quantity of bandwidth in GB for an individual CDN. Regions might differ for each vendor, per mapping.



* Parameters:



* mappingUniqueId - Provide a unique ID of the mapping for which metrics are queried.
* startDate - Provide the start date timestamp (UTC+0) for query.
* endDate - Provide the end date timestamp (UTC+0) for query.
* frequency - Provide the data frequency for data format, the following options are available to configure frequency:



* aggregate - Aggregated metrics data from startDate to endDatedefault.
* day - Daily metrics data from startDate to endDate.





* Return - A collection of objects of type SoftLayer_Container_Network_CdnMarketplace_Metrics.
Metrics container 

The SoftLayer_Container_Network_CdnMarketplace_Metrics collection contains the attributes that are used by our Metrics APIs. There are three possible values for the type attribute: PIECHART, LINEGRAPH, or TOTALS. The output for the rest of the attributes in this container depend on the type, which is described in further detail. All attributes except type are arrays. Not all attributes are used for all types.

classSoftLayer_Container_Network_CdnMarketplace_Metrics:



*  type
*  names
*  totals
*  percentage
*  time
*  xaxis
*  yaxis
*  yaxis2
*  yaxis3
*  yaxis4
*  yaxis5
*  yaxis6
*  yaxis7
*  yaxis8
*  yaxis9
*  yaxis10
*  yaxis11
*  yaxis12
*  yaxis13
*  yaxis14
*  yaxis15
*  yaxis16
*  yaxis17
*  yaxis18
*  yaxis19
*  yaxis20



The PIECHART type is for data that is sent to a pie chart. In this case, the only attributes that are used are: names, xaxis, and yaxis. The names attribute is an array containing the region names. The xaxis attribute contains the usage in GB, and yaxis1 is the test percentage.

The LINEGRAPH type is for data that will be sent to a line graph. In this case, the names array ontains the names of the metrics that are found in the xaxis, yaxis, yaxis2...yaxis20 attributes, and the actual data is in the corresponding arrays.

If type is TOTALS, the names array contains the names of the metrics that are found in the corresponding totals array, and the actual data is contained in the totals array.
The metric ipmi_sel_free_space_bytes reports the number of free bytes for new ystem event log entries.
* IPMI sensor data

The IPMI exporter collects 2 metrics per sensor type: state and value. A value of 0 reports a normal state. A value of 1 reports a warning state. A value of 2 reports a critical state. A value of NaN reports information not available. For example, see the metrics for different sensors:

Temperature sensor metrics: ipmi_temperature_celsius, ipmi_temperature_state

Fan speed sensor metrics: ipmi_fan_speed_rpm, ipmi_fan_speed_state

Voltage sensor metrics: ipmi_voltage_state, ipmi_voltage_volts
* IPMI chassis power state of the machine

The metric ipmi_chassis_power_state informs about the current state of the chassis of the machine. It has a value of 1 when the power is on. It has a value of 0 when the power is off.
* DCMI data

The metric ipmi_dcmi_power_consumption_current_watts informs about the live power consumption of the machine in Watts.
* BMC details

The metric ipmi_bmc_info includes information about the firmware revision and manufacturer in labels and has a value of 1.



For more information, see [Prometheus IPMI Exporter](https://github.com/soundcloud/ipmi_exporter).

To learn how to configure the IPMI exporter, see [Configuring the Prometheus IPMI Exporter to monitor sensor metrics](https://cloud.ibm.com/docs/monitoring?topic=monitoring-ipmi).

You can also check the tutorial: [Configure the Prometheus IPMI Exporter to monitor sensor metrics in a Bare metal](https://cloud.ibm.com/docs/monitoring?topic=monitoring-baremetal_linuxbaremetal_linux_step3).





 Blackbox exporter 

Allows blackbox probing of endpoints over HTTP, HTTPS, DNS, TCP and ICMP.