vania-janet/multiturn-rag-retrieval-data huggingface dataset:
The following Bosnian translation model can be customized.



Table 5. Bosnian translation model

 Model ID Source Target Domain 

 bs-en Bosnian (bs) English (en) general 







 Bulgarian 

The following Bulgarian translation model can be customized.



Table 6. Bulgarian translation model

 Model ID Source Target Domain 

 bg-en Bulgarian (bg) English (en) general 







 Catalan 

The following Catalan translation model can be customized.



Table 7. Catalan translation model

 Model ID Source Target Domain 

 ca-es Catalan (ca) Spanish (es) general 







 Chinese (Simplified) 

The following Chinese (Simplified) translation model can be customized.



Table 8. Simplified Chinese translation model

 Model ID Source Target Domain 

 zh-en Simplified Chinese (zh) English (en) general 







 Chinese (Traditional) 

The following Chinese (Traditional) translation model can be customized.



Table 9. Traditional Chinese translation model

 Model ID Source Target Domain 

 zh-TW-en Simplified Chinese (zh-TW) English (en) general 







 Croatian 

The following Croatian translation model can be customized.



Table 10. Croatian translation model

 Model ID Source Target Domain 

 hr-en Croatian (hr) English (en) general 







 Czech 

The following Czech translation model can be customized.



Table 11. Czech translation model

 Model ID Source Target Domain 

 cs-en Czech (cs) English (en) general 







 Danish 

The following Danish translation model can be customized.



Table 12. Danish translation model

 Model ID Source Target Domain 

 da-en Danish (da) English (en) general 







 Dutch 

The following Dutch translation model can be customized.



Table 13. Dutch translation model

 Model ID Source Target Domain 

 nl-en Dutch (nl) English (en) general 







 English 

The following English translation models can be customized.

The English-to-Montenegrin translation model (en-cnr) is not customizable at this time. It can be used for translation but cannot be customized.



Table 14. English translation models

 Model ID Source Target Domain
Portuguese (Brazilian) pt-BR_NarrowbandModel GA <br>Deprecated pt-BR_Telephony 
 Spanish (Argentinian, Beta) es-AR_NarrowbandModel Beta <br>Deprecated es-LA_Telephony 
 Spanish (Castilian) es-ES_NarrowbandModel GA <br>Deprecated es-ES_Telephony 
 Spanish (Chilean, Beta) es-CL_NarrowbandModel Beta <br>Deprecated es-LA_Telephony 
 Spanish (Colombian, Beta) es-CO_NarrowbandModel Beta <br>Deprecated es-LA_Telephony 
 Spanish (Mexican, Beta) es-MX_NarrowbandModel Beta <br>Deprecated es-LA_Telephony 
 Spanish (Peruvian, Beta) es-PE_NarrowbandModel Beta <br>Deprecated es-LA_Telephony 







 Broadband models 

Table 2 lists the previous-generation broadband models that are available.



Table 2. Supported previous-generation broadband models

 Language Model name Status Recommended next-generation model 

 Arabic (Modern Standard) ar-MS_BroadbandModel GA <br>Deprecated ar-MS_Telephony 
 Chinese (Mandarin) zh-CN_BroadbandModel GA <br>Deprecated zh-CN_Telephony 
 Dutch (Netherlands) nl-NL_BroadbandModel GA <br>Deprecated nl-NL_Multimedia 
 English (Australian) en-AU_BroadbandModel GA <br>Deprecated en-AU_Multimedia 
 English (United Kingdom) en-GB_BroadbandModel GA <br>Deprecated en-GB_Multimedia 
 English (United States) en-US_BroadbandModel GA <br>Deprecated en-US_Multimedia 
 French (Canadian) fr-CA_BroadbandModel GA <br>Deprecated fr-CA_Multimedia 
 French (France) fr-FR_BroadbandModel GA <br>Deprecated fr-FR_Multimedia 
 German de-DE_BroadbandModel GA <br>Deprecated de-DE_Multimedia 
 Italian it-IT_BroadbandModel GA <br>Deprecated it-IT_Multimedia
The Montenegrin-to-English translation model (cnr-en) is not customizable at this time. It can be used for translation but cannot be customized.





 Nepali 

The following Nepali translation model can be customized.



Table 38. Nepali translation model

 Model ID Source Target Domain 

 ne-en Nepali (ne) English (en) general 







 Norwegian Bokmål 

The following Norwegian Bokmål translation model can be customized.



Table 39. Norwegian Bokmål translation model

 Model ID Source Target Domain 

 nb-en Norwegian Bokmål (nb) English (en) general 







 Polish 

The following Polish translation model can be customized.



Table 40. Polish translation model

 Model ID Source Target Domain 

 pl-en Polish (pl) English (en) general 







 Portuguese 

The following Portuguese translation model can be customized.



Table 41. Portuguese translation model

 Model ID Source Target Domain 

 pt-en Portuguese (pt) English (en) general 







 Punjabi (Indian) 

The following Indian Punjabi translation model can be customized.



Table 42. Indian Punjabi translation model

 Model ID Source Target Domain 

 pa-en Indian Punjabi (pa) English (en) general 







 Punjabi (Pakistani) 

The following Pakistani Punjabi (Shahmukhi script) translation model can be customized.



Table 43. Pakistani Punjabi translation model

 Model ID Source Target Domain 

 pa-PK-en Pakistani Punjabi (pa-PK) English (en) general 







 Romanian 

The following Romanian translation model can be customized.



Table 44. Romanian translation model

 Model ID Source Target Domain 

 ro-en Romanian (ro) English (en) general 







 Russian 

The following Russian translation model can be customized.



Table 45. Russian translation model

 Model ID Source Target Domain 

 ru-en Russian (ru) English (en) general 







 Serbian 

The following Serbian translation model can be customized. The service supports translation for Serbian based on the Cyrillic alphabet, not the Latin alphabet.



Table 46. Serbian translation model

 Model ID Source Target Domain 

 sr-en Serbian (sr) English (en) general 







 Sinhala
Narrowband models 

Table 1 lists the previous-generation narrowband models that are available.



Table 1. Supported previous-generation narrowband models

 Language Model name Status Recommended next-generation model 

 Chinese (Mandarin) zh-CN_NarrowbandModel GA <br>Deprecated zh-CN_Telephony 
 Dutch (Netherlands) nl-NL_NarrowbandModel GA <br>Deprecated nl-NL_Telephony 
 English (Australian) en-AU_NarrowbandModel GA <br>Deprecated en-AU_Telephony 
 English (United Kingdom) en-GB_NarrowbandModel GA <br>Deprecated en-GB_Telephony 
 English (United States) en-US_NarrowbandModel GA <br>Deprecated en-US_Telephony 
 en-US_ShortForm_NarrowbandModel GA <br>Deprecated en-US_Telephony 
 French (Canadian) fr-CA_NarrowbandModel GA <br>Deprecated fr-CA_Telephony 
 French (France) fr-FR_NarrowbandModel GA <br>Deprecated fr-FR_Telephony 
 German de-DE_NarrowbandModel GA <br>Deprecated de-DE_Telephony 
 Italian it-IT_NarrowbandModel GA <br>Deprecated it-IT_Telephony 
 Japanese ja-JP_NarrowbandModel GA <br>Deprecated ja-JP_Telephony <br><br>IBM Cloud 
 Korean ko-KR_NarrowbandModel GA <br>Deprecated ko-KR_Telephony 
 Portuguese (Brazilian) pt-BR_NarrowbandModel GA <br>Deprecated pt-BR_Telephony 
 Spanish (Argentinian, Beta) es-AR_NarrowbandModel Beta <br>Deprecated es-LA_Telephony 
 Spanish (Castilian) es-ES_NarrowbandModel GA <br>Deprecated es-ES_Telephony 
 Spanish (Chilean, Beta) es-CL_NarrowbandModel Beta <br>Deprecated es-LA_Telephony
[External link icon](https://cloud.ibm.com/docs-content/v1/content/ded4adc3ea0bd2a81b113c579f2b1183926da211/icons/launch-glyph.svg)](https://watson-developer-cloud.github.io/doc-tutorial-downloads/discovery/custom_stopwords_en.txt). It can be used as a starting point when building a custom stopword list in English. Creating a custom stopword list that does not include very common terms like a and the can lead to reduced query performance, so it is recommended that you keep these words in your custom stopword list. Following are stopword lists for several other supported languages. They all include the default stopwords for that language:



* Dutch: [custom_stopwords_nl.txt ![External link icon](https://cloud.ibm.com/docs-content/v1/content/ded4adc3ea0bd2a81b113c579f2b1183926da211/icons/launch-glyph.svg)](https://watson-developer-cloud.github.io/doc-tutorial-downloads/discovery/custom_stopwords_nl.txt).
* French: [custom_stopwords_fr.txt ![External link icon](https://cloud.ibm.com/docs-content/v1/content/ded4adc3ea0bd2a81b113c579f2b1183926da211/icons/launch-glyph.svg)](https://watson-developer-cloud.github.io/doc-tutorial-downloads/discovery/custom_stopwords_fr.txt).
* German: [custom_stopwords_de.txt !
Show more





 Example 2 

This example shows you how to translate a message response back to the customer's native language. It only works if you perform the steps in [Example 2](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-webhook-prewebhook-pre-example-translate) to define a premessage webhook that translates the original message into English.

Define a sequence of web actions in IBM Cloud Functions. The first action in the sequence checks for the language of the original incoming text, which you stored in a context variable named original_input in the premessage webhook code. The second action in the sequence translates the dialog response text from English into the original language that was used by the customer.

In the premessage webhook configuration page, the following values are specified:



* URL: https://us-south.functions.appdomain.cloud/api/v1/web/e97d2516-5ce4-4fd9-9d05-acc3dd8ennn/default/response-translation_sequence
* Secret: none
* Header name: Content-Type
* Header value: application/json



The node.js code for the first web action in your sequence looks as follows:

let rp = require("request-promise");

function main(params) {
console.log(JSON.stringify(params))

if (params.payload.output.generic[0].text !== '') {
const options = { method: 'POST',
url: 'https://api.us-south.language-translator.watson.cloud.ibm.com/instances/572b37be-09f4-4704-b693-3bc63869nnnn/v3/identify?version=2018-05-01',
auth: {
'username': 'apikey',
'password': 'nnnn'
},
headers: {
"Content-Type":"text/plain"
},
Multiple neural voice improvements
: The existing neural voices for Chinese, Dutch (Belgian and Netherlands), Australian English, and Korean have been updated for improved speech synthesis and enhanced audio results. For more information about all available voices, see [Languages and voices](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-voices).

New Australian English neural voice: en-AU_SteveVoice
: A new male Australian English voice, en-AU_SteveVoice, is now available. The voice is a neural voice.

New Swedish neural voice: sv-SE_IngridVoice
: A new language, Swedish, with a new female voice, sv-SE_IngridVoice, is now available. The voice is a neural voice.





 6 October 2021 

New US HIPAA support for Premium plans in Dallas location
: US Health Insurance Portability and Accountability Act (HIPAA) support is now available for Premium plans that are hosted in the Dallas (us-south) location. For more information, see [Health Insurance Portability and Accountability Act (HIPAA)](https://cloud.ibm.com/docs/text-to-speech?topic=text-to-speech-information-securityhipaa).

Defect fix: Improve Latin American Spanish enhanced neural voice
: Defect fix: For the Latin American Spanish voice (es-LA_SofiaV3Voice), questions of all types now use the correct intonation.





 16 September 2021 

Defect fix: Improve Castilian Spanish and North American Spanish enhanced neural voices
: Defect fix: For the Castilian Spanish (es-ES_EnriqueV3Voice and es-ES_LauraV3Voice) and North American Spanish (es-US_SofiaV3Voice) voices, questions of all types now use the correct intonation. For the Latin American Spanish voice (es-LA_SofiaV3Voice), some questions do not use the correct intonation and sound instead like statements. The Latin American Spanish voice will be fixed soon.





 16 July 2021 

New Belgian Dutch neural voice: nl-BE_AdeleVoice
: The service now supports Belgian Dutch (Flemish) with the neural voice nl-BE_AdeleVoice.
}
Show more





 Example 2 

This example shows you how to translate a message response back to the customer's native language. It only works if you perform the steps in [Example 2](https://cloud.ibm.com/docs/assistant-data?topic=assistant-webhook-prewebhook-pre-example-translate) to define a premessage webhook that translates the original message into English.

Define a sequence of web actions in IBM Cloud Functions. The first action in the sequence checks for the language of the original incoming text, which you stored in a context variable named original_input in the premessage webhook code. The second action in the sequence translates the dialog response text from English into the original language that was used by the customer.

In the premessage webhook configuration page, the following values are specified:



* URL: https://us-south.functions.appdomain.cloud/api/v1/web/e97d2516-5ce4-4fd9-9d05-acc3dd8ennn/default/response-translation_sequence
* Secret: none
* Header name: Content-Type
* Header value: application/json



The node.js code for the first web action in your sequence looks as follows:

let rp = require("request-promise");

function main(params) {
console.log(JSON.stringify(params))

if (params.payload.output.generic[0].text !== '') {
const options = { method: 'POST',
url: 'https://api.us-south.language-translator.watson.cloud.ibm.com/instances/572b37be-09f4-4704-b693-3bc63869nnnn/v3/identify?version=2018-05-01',
auth: {
'username': 'apikey',
'password': 'nnnn'
},
headers: {
"Content-Type":"text/plain"
},
}
}
Show more





 Example 2 

This example shows you how to translate a message response back to the customer's native language. It only works if you perform the steps in [Example 2](https://cloud.ibm.com/docs/assistant?topic=assistant-webhook-prewebhook-pre-example-translate) to define a premessage webhook that translates the original message into English.

Define a sequence of web actions in IBM Cloud Functions. The first action in the sequence checks for the language of the original incoming text, which you stored in a context variable named original_input in the premessage webhook code. The second action in the sequence translates the dialog response text from English into the original language that was used by the customer.

In the premessage webhook configuration page, the following values are specified:



* URL: https://us-south.functions.appdomain.cloud/api/v1/web/e97d2516-5ce4-4fd9-9d05-acc3dd8ennn/default/response-translation_sequence
* Secret: none
* Header name: Content-Type
* Header value: application/json



The node.js code for the first web action in your sequence looks as follows:

let rp = require("request-promise");

function main(params) {
console.log(JSON.stringify(params))

if (params.payload.output.generic[0].text !== '') {
const options = { method: 'POST',
url: 'https://api.us-south.language-translator.watson.cloud.ibm.com/instances/572b37be-09f4-4704-b693-3bc63869nnnn/v3/identify?version=2018-05-01',
auth: {
'username': 'apikey',
'password': 'nnnn'
},
headers: {
"Content-Type":"text/plain"
: The service now offers beta broadband and narrowband models for the Netherlands Dutch language:



* nl-NL_BroadbandModel
* nl-NL_NarrowbandModel



These language models support acoustic model customization. They do not support language model customization. Because they are beta, these models might not be ready for production use and are subject to change. They are initial offerings that are expected to improve in quality with time and usage.

For more information, see the following sections:



* [Supported previous-generation language models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-modelsmodels-supported)
* [Language support for customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support)







 25 November 2019 

Updates to speaker labels for improved identification of individual speakers
: Speaker labels are updated to improve the identification of individual speakers for further analysis of your audio sample. For more information about the speaker labels feature, see [Speaker labels](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-speaker-labels). For more information about the improvements to the feature, see [IBM Research AI Advances Speaker Diarization in Real Use Cases](https://www.ibm.com/blogs/research/2020/07/speaker-diarization-in-real-use-cases/).





 12 November 2019 

New Seoul location now available
: The Speech to Text service is now available in the IBM Cloud Seoul location (kr-seo). As with other locations, the IBM Cloud location uses token-based IAM authentication. All new services instances that you create in this location use IAM authentication.





 1 November 2019 

New limits on maximum number of custom models
: You can create no more than 1024 custom language models and no more than 1024 custom acoustic models per owning credentials.
ta-en Tamil (ta) English (en) general 







 Telugu 

The following Telugu translation model can be customized.



Table 53. Telugu translation model

 Model ID Source Target Domain 

 te-en Telugu (te) English (en) general 







 Thai 

The following Thai translation model can be customized.



Table 54. Thai translation model

 Model ID Source Target Domain 

 th-en Thai (th) English (en) general 







 Turkish 

The following Turkish translation model can be customized.



Table 55. Turkish translation model

 Model ID Source Target Domain 

 tr-en Turkish (tr) English (en) general 







 Ukrainian 

The following Ukrainian translation model can be customized.



Table 56. Ukrainian translation model

 Model ID Source Target Domain 

 uk-en Ukrainian (uk) English (en) general 







 Urdu 

The following Urdu translation model can be customized.



Table 57. Urdu translation model

 Model ID Source Target Domain 

 ur-en Urdu (ur) English (en) general 







 Vietnamese 

The following Vietnamese translation model can be customized.



Table 58. Vietnamese translation model

 Model ID Source Target Domain 

 vi-en Vietnamese (vi) English (en) general 







 Welsh 

The following Welsh translation model can be customized.



Table 59. Welsh translation model

 Model ID Source Target Domain 

 cy-en Welsh (cy) English (en) general
Dutch $100 becomes honderd dollar €100 becomes honderd euro 100% becomes honderd procent 
 English $100 becomes one hundred dollars €100 becomes one hundred euros 100% becomes one hundred percent 
 French $100 becomes cent dollars €100 becomes cent euros 100% becomes cent pour cent 
 German $100 and 100$ become einhundert dollar €100 and 100€ become einhundert euro 100% becomes einhundert prozent 
 Italian $100 becomes cento dollari €100 becomes cento euro 100% becomes cento per cento 
 Portuguese $100 and 100$ become cem dólares €100 and 100€ become cem euros 100% becomes cem por cento 
 Spanish $100 and 100$ become cien dólares €100 and 100€ become cien euros 100% becomes cien por ciento 



* Processes non-alphanumeric, punctuation, and special characters depending on their context. For example, the service removes a $ (dollar sign) or € (euro symbol) unless it is followed by a number. Processing is context-dependent and consistent across the supported languages.
* Ignores phrases that are enclosed in ( ) (parentheses), < > (angle brackets), [ ] (square brackets), or { } (curly braces).







 Parsing of Japanese 



* Converts all characters to full-width characters.
* Converts numbers to their equivalent words, for example, 500 becomes 五百, and 0.15 becomes 〇・一五.
* Does not convert tokens that include symbols to equivalent strings, for example, 100% becomes 百％.
* Does not automatically remove punctuation. IBM highly recommends that you remove punctuation if your application is transcription-based as opposed to dictation-based.







 Parsing of Korean 



* Converts numbers to their equivalent words, for example, 10 becomes 십.
* Removes the following punctuation and special characters: - ( ) : . , ' ". However, not all punctuation and special characters that are removed for other languages are removed for Korean, for example:



* Removes a period (.) symbol only when it occurs at the end of a line of input.
* Does not remove a tilde () symbol.
: The next-generation US English en-US_Telephony model has been updated for improved speech recognition. The updated model continues to be beta functionality.

Defect fix: Update documentation for hesitation markers
: Defect fix: The documentation failed to state that next-generation models do not produce hesitation markers. The documentation has been updated to note that only previous-generation models produce hesitation markers. Next-generation models include the actual hesitations in 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).





 15 June 2021 

New beta Belgian Dutch next-generation model
: The Belgian Dutch (Flemish) next-generation language model nl-BE_Telephony is now available. The new model supports low latency. The model is beta functionality. For more information about the next-generation models and about low latency, see [Next-generation languages and models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng) and [Low latency](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-interimlow-latency).

New beta low-latency support for Arabic, Canadian French, and Italian next-generation models
: The following existing beta next-generation language models now support low latency:



* Arabic ar-MS_Telephony model
* Canadian French fr-CA_Telephony model
* Italian it-IT_Telephony model



For more information about the next-generation models and about low latency, see [Next-generation languages and models](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-models-ng) and [Low latency](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-interimlow-latency).

Updates to beta Arabic and Brazilian Portuguese next-generation models for improved speech recognition
Danish [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2) [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2) [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2) [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2) [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2) [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2) [Version 2](https://cloud.ibm.com/docs/natural-language-understanding/?topic=natural-language-understanding-entity-types-version-2)