use of com.ibm.watson.speech_to_text.v1.model.TrainingResponse in project java-sdk by watson-developer-cloud.
the class SpeechToText method trainLanguageModel.
/**
* Train a custom language model.
*
* <p>Initiates the training of a custom language model with new resources such as corpora,
* grammars, and custom words. After adding, modifying, or deleting resources for a custom
* language model, use this method to begin the actual training of the model on the latest data.
* You can specify whether the custom language model is to be trained with all words from its
* words resource or only with words that were added or modified by the user directly. You must
* use credentials for the instance of the service that owns a model to train it.
*
* <p>The training method is asynchronous. It can take on the order of minutes to complete
* depending on the amount of data on which the service is being trained and the current load on
* the service. The method returns an HTTP 200 response code to indicate that the training process
* has begun.
*
* <p>You can monitor the status of the training by using the [Get a custom language
* model](#getlanguagemodel) method to poll the model's status. Use a loop to check the status
* every 10 seconds. The method returns a `LanguageModel` object that includes `status` and
* `progress` fields. A status of `available` means that the custom model is trained and ready to
* use. The service cannot accept subsequent training requests or requests to add new resources
* until the existing request completes.
*
* <p>**See also:** * [Train the custom language
* model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-languageCreate#trainModel-language)
* * [Language support for
* customization](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-custom-support)
*
* <p>### Training failures
*
* <p>Training can fail to start for the following reasons: * The service is currently handling
* another request for the custom model, such as another training request or a request to add a
* corpus or grammar to the model. * No training data have been added to the custom model. * The
* custom model contains one or more invalid corpora, grammars, or words (for example, a custom
* word has an invalid sounds-like pronunciation). You can correct the invalid resources or set
* the `strict` parameter to `false` to exclude the invalid resources from the training. The model
* must contain at least one valid resource for training to succeed.
*
* @param trainLanguageModelOptions the {@link TrainLanguageModelOptions} containing the options
* for the call
* @return a {@link ServiceCall} with a result of type {@link TrainingResponse}
*/
public ServiceCall<TrainingResponse> trainLanguageModel(TrainLanguageModelOptions trainLanguageModelOptions) {
com.ibm.cloud.sdk.core.util.Validator.notNull(trainLanguageModelOptions, "trainLanguageModelOptions cannot be null");
Map<String, String> pathParamsMap = new HashMap<String, String>();
pathParamsMap.put("customization_id", trainLanguageModelOptions.customizationId());
RequestBuilder builder = RequestBuilder.post(RequestBuilder.resolveRequestUrl(getServiceUrl(), "/v1/customizations/{customization_id}/train", pathParamsMap));
Map<String, String> sdkHeaders = SdkCommon.getSdkHeaders("speech_to_text", "v1", "trainLanguageModel");
for (Entry<String, String> header : sdkHeaders.entrySet()) {
builder.header(header.getKey(), header.getValue());
}
builder.header("Accept", "application/json");
if (trainLanguageModelOptions.wordTypeToAdd() != null) {
builder.query("word_type_to_add", String.valueOf(trainLanguageModelOptions.wordTypeToAdd()));
}
if (trainLanguageModelOptions.customizationWeight() != null) {
builder.query("customization_weight", String.valueOf(trainLanguageModelOptions.customizationWeight()));
}
ResponseConverter<TrainingResponse> responseConverter = ResponseConverterUtils.getValue(new com.google.gson.reflect.TypeToken<TrainingResponse>() {
}.getType());
return createServiceCall(builder.build(), responseConverter);
}
use of com.ibm.watson.speech_to_text.v1.model.TrainingResponse in project java-sdk by watson-developer-cloud.
the class SpeechToTextTest method testTrainAcousticModelWOptions.
// Test the trainAcousticModel operation with a valid options model parameter
@Test
public void testTrainAcousticModelWOptions() throws Throwable {
// Register a mock response
String mockResponseBody = "{\"warnings\": [{\"code\": \"invalid_audio_files\", \"message\": \"message\"}]}";
String trainAcousticModelPath = "/v1/acoustic_customizations/testString/train";
server.enqueue(new MockResponse().setHeader("Content-type", "application/json").setResponseCode(200).setBody(mockResponseBody));
// Construct an instance of the TrainAcousticModelOptions model
TrainAcousticModelOptions trainAcousticModelOptionsModel = new TrainAcousticModelOptions.Builder().customizationId("testString").customLanguageModelId("testString").build();
// Invoke trainAcousticModel() with a valid options model and verify the result
Response<TrainingResponse> response = speechToTextService.trainAcousticModel(trainAcousticModelOptionsModel).execute();
assertNotNull(response);
TrainingResponse responseObj = response.getResult();
assertNotNull(responseObj);
// Verify the contents of the request sent to the mock server
RecordedRequest request = server.takeRequest();
assertNotNull(request);
assertEquals(request.getMethod(), "POST");
// Verify request path
String parsedPath = TestUtilities.parseReqPath(request);
assertEquals(parsedPath, trainAcousticModelPath);
// Verify query params
Map<String, String> query = TestUtilities.parseQueryString(request);
assertNotNull(query);
assertEquals(query.get("custom_language_model_id"), "testString");
}
use of com.ibm.watson.speech_to_text.v1.model.TrainingResponse in project java-sdk by watson-developer-cloud.
the class SpeechToTextTest method testTrainLanguageModelWOptions.
// Test the trainLanguageModel operation with a valid options model parameter
@Test
public void testTrainLanguageModelWOptions() throws Throwable {
// Register a mock response
String mockResponseBody = "{\"warnings\": [{\"code\": \"invalid_audio_files\", \"message\": \"message\"}]}";
String trainLanguageModelPath = "/v1/customizations/testString/train";
server.enqueue(new MockResponse().setHeader("Content-type", "application/json").setResponseCode(200).setBody(mockResponseBody));
// Construct an instance of the TrainLanguageModelOptions model
TrainLanguageModelOptions trainLanguageModelOptionsModel = new TrainLanguageModelOptions.Builder().customizationId("testString").wordTypeToAdd("all").customizationWeight(Double.valueOf("72.5")).build();
// Invoke trainLanguageModel() with a valid options model and verify the result
Response<TrainingResponse> response = speechToTextService.trainLanguageModel(trainLanguageModelOptionsModel).execute();
assertNotNull(response);
TrainingResponse responseObj = response.getResult();
assertNotNull(responseObj);
// Verify the contents of the request sent to the mock server
RecordedRequest request = server.takeRequest();
assertNotNull(request);
assertEquals(request.getMethod(), "POST");
// Verify request path
String parsedPath = TestUtilities.parseReqPath(request);
assertEquals(parsedPath, trainLanguageModelPath);
// Verify query params
Map<String, String> query = TestUtilities.parseQueryString(request);
assertNotNull(query);
assertEquals(query.get("word_type_to_add"), "all");
assertEquals(Double.valueOf(query.get("customization_weight")), Double.valueOf("72.5"));
}
use of com.ibm.watson.speech_to_text.v1.model.TrainingResponse in project java-sdk by watson-developer-cloud.
the class SpeechToText method trainAcousticModel.
/**
* Train a custom acoustic model.
*
* <p>Initiates the training of a custom acoustic model with new or changed audio resources. After
* adding or deleting audio resources for a custom acoustic model, use this method to begin the
* actual training of the model on the latest audio data. The custom acoustic model does not
* reflect its changed data until you train it. You must use credentials for the instance of the
* service that owns a model to train it.
*
* <p>The training method is asynchronous. Training time depends on the cumulative amount of audio
* data that the custom acoustic model contains and the current load on the service. When you
* train or retrain a model, the service uses all of the model's audio data in the training.
* Training a custom acoustic model takes approximately as long as the length of its cumulative
* audio data. For example, it takes approximately 2 hours to train a model that contains a total
* of 2 hours of audio. The method returns an HTTP 200 response code to indicate that the training
* process has begun.
*
* <p>You can monitor the status of the training by using the [Get a custom acoustic
* model](#getacousticmodel) method to poll the model's status. Use a loop to check the status
* once a minute. The method returns an `AcousticModel` object that includes `status` and
* `progress` fields. A status of `available` indicates that the custom model is trained and ready
* to use. The service cannot train a model while it is handling another request for the model.
* The service cannot accept subsequent training requests, or requests to add new audio resources,
* until the existing training request completes.
*
* <p>You can use the optional `custom_language_model_id` parameter to specify the GUID of a
* separately created custom language model that is to be used during training. Train with a
* custom language model if you have verbatim transcriptions of the audio files that you have
* added to the custom model or you have either corpora (text files) or a list of words that are
* relevant to the contents of the audio files. For training to succeed, both of the custom models
* must be based on the same version of the same base model, and the custom language model must be
* fully trained and available.
*
* <p>**Note:** Acoustic model customization is supported only for use with previous-generation
* models. It is not supported for next-generation models.
*
* <p>**See also:** * [Train the custom acoustic
* model](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-acoustic#trainModel-acoustic)
* * [Using custom acoustic and custom language models
* together](https://cloud.ibm.com/docs/speech-to-text?topic=speech-to-text-useBoth#useBoth)
*
* <p>### Training failures
*
* <p>Training can fail to start for the following reasons: * The service is currently handling
* another request for the custom model, such as another training request or a request to add
* audio resources to the model. * The custom model contains less than 10 minutes or more than 200
* hours of audio data. * You passed a custom language model with the `custom_language_model_id`
* query parameter that is not in the available state. A custom language model must be fully
* trained and available to be used to train a custom acoustic model. * You passed an incompatible
* custom language model with the `custom_language_model_id` query parameter. Both custom models
* must be based on the same version of the same base model. * The custom model contains one or
* more invalid audio resources. You can correct the invalid audio resources or set the `strict`
* parameter to `false` to exclude the invalid resources from the training. The model must contain
* at least one valid resource for training to succeed.
*
* @param trainAcousticModelOptions the {@link TrainAcousticModelOptions} containing the options
* for the call
* @return a {@link ServiceCall} with a result of type {@link TrainingResponse}
*/
public ServiceCall<TrainingResponse> trainAcousticModel(TrainAcousticModelOptions trainAcousticModelOptions) {
com.ibm.cloud.sdk.core.util.Validator.notNull(trainAcousticModelOptions, "trainAcousticModelOptions cannot be null");
Map<String, String> pathParamsMap = new HashMap<String, String>();
pathParamsMap.put("customization_id", trainAcousticModelOptions.customizationId());
RequestBuilder builder = RequestBuilder.post(RequestBuilder.resolveRequestUrl(getServiceUrl(), "/v1/acoustic_customizations/{customization_id}/train", pathParamsMap));
Map<String, String> sdkHeaders = SdkCommon.getSdkHeaders("speech_to_text", "v1", "trainAcousticModel");
for (Entry<String, String> header : sdkHeaders.entrySet()) {
builder.header(header.getKey(), header.getValue());
}
builder.header("Accept", "application/json");
if (trainAcousticModelOptions.customLanguageModelId() != null) {
builder.query("custom_language_model_id", String.valueOf(trainAcousticModelOptions.customLanguageModelId()));
}
ResponseConverter<TrainingResponse> responseConverter = ResponseConverterUtils.getValue(new com.google.gson.reflect.TypeToken<TrainingResponse>() {
}.getType());
return createServiceCall(builder.build(), responseConverter);
}
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