Rev AI Java SDK

Documentation

See the API docs for more information about the API.

Install the SDK

The recommended way to use the Rev AI Java SDK is to import it into the project using Maven.

  <dependency>
    <groupId>ai.rev</groupId>
    <artifactId>revai-java-sdk</artifactId>
    <version>2.2.0</version>
  </dependency>

Build and install locally from source

Once you've cloned the repo you can use Maven to build it locally and install it in your local Maven .m2 repository.

mvn install -DskipTests=true      

Support

We support Java 8 and 11.

Usage

All you need to get started is your Access Token, which can be generated on your Settings Page. Create a client with the given Access Token:

// Initialize your client with your Rev AI access token
String accessToken = "Your Access Token";
ApiClient apiClient = new ApiClient(accessToken);

Checking credits remaining

RevAiAccount revAiAccount = apiClient.getAccount();

Submitting a job

You can submit a local file

String localPathToFile = "./path/to/file.mp3";
RevAiJob revAiJob = apiClient.submitJobLocalFile(localPathToFile);

or submit via a public direct download url

String urlLinkToFile = "https://www.rev.ai/FTC_Sample_1.mp3";
RevAiJob revAiJob = apiClient.submitJobUrl(urlLinkToFile);

or from FileInputStream, the filename is optional.

File file = new File("./path/to/file.mp3");
FileInputStream fileInputStream;
try {
  fileInputStream = new FileInputStream(file);
} catch (FileNotFoundException e) {
  throw new RuntimeException("Could not find file [" + file.getName() + "]");
}
RevAiJob revAiJob = apiClient.submitJobLocalFile(fileInputStream, String fileName, RevAiJobOptions options);

You can also submit a job to be handled by a human transcriber using our Human Transcription option.

String urlLinkToFile = "https://www.rev.ai/FTC_Sample_1.mp3";
RevAiJobOptions options = new RevAiJobOptions();

// set to perform human transcription
options.setTranscriber("human");

// optional job options
options.setVerbatim(true);
options.setRush(false);
options.setTestMode(true);

// optional segments to transcribe
SegmentToTranscribe segment = new SegmentToTranscribe();
segment.setStartTimestamp(2.0);
segment.setEndTimestamp(100.5);
options.setSegmentsToTranscribe(List.of(segment));

// optional speaker names 
SpeakerName speaker = new SpeakerName();
speaker.setDisplayName('Alan Mathison Turing');
options.setSpeakerNames(List.of(speaker));

RevAiJob revAiJob = apiClient.submitJobUrl(urlLinkToFile, options);

RevAiJob objects contain job information as defined by the documentation.

If you want to get fancy, all submit job methods have overrides that allow specifying RevAiJobOptions to configure job specific settings. In RevAiJobOptions, you could include metadata,notification_config, skip_diarization, skip_punctuation, speaker_channels_count,custom_vocabularies, filter_profanity, remove_disfluencies, delete_after_seconds, and language as optional parameters.

The url submission option also supports authentication headers by using the source_config option.

All options are described in the request body of the Submit Job endpoint.

Checking your job's status

You can check the status of your transcription job using its id

RevAiJob newlyRefreshedRevAiJob = apiClient.getJobDetails(revAiJob.getJobId());

RevAiJob objects contain job information as defined by the documentation.

Checking multiple files

You can retrieve a list of transcription jobs with optional parameters

List<RevAiJob> jobs = apiClient.getListOfJobs();

// limit amount of retrieved jobs
int numberOfJobsToReturn = 3;
List<RevAiJob> jobs = apiClient.getListOfJobs(numberOfJobsToReturn);

// get jobs starting after a certain job ID
String jobId = "Umx5c6F7pH7r";
List<RevAiJob> jobs = apiClient.getListOfJobs(jobId);

jobs will contain a list of RevAiJob objects, having all information normally found in a successful response from our Get List of Jobs endpoint

Deleting a job

You can delete a transcription job using its id

apiClient.deleteJob(revAiJob.getJobId());

All data related to the job, such as input media and transcript, will be permanently deleted. A job can only by deleted once it's completed (either with success or failure).

Getting your transcript

Once your file is transcribed, you can get your transcript in a few different forms:

// as plain text
String transcriptText = apiClient.getTranscriptText(revAiJob.getJobId());

// or as an object
RevAiTranscript revAiTranscript = apiClient.getTranscriptObject(revAiJob.getJobId());

The text output is a string containing just the text of your transcript. The object form of the transcript contains all the information outlined in the response of the Get Transcript endpoint when using the json response schema.

Getting captions output

Another way to retrieve your file is captions output. We support both .srt and .vtt outputs. See below for an example showing how you can get captions as a readable stream. If your job was submitted with multiple speaker channels you are required to provide the id of the channel you would like captioned.

InputStream inputStream = apiClient.getCaptions(revAiJob.getJobId(), RevAiCaptionType.SRT);

// with speaker channels
int channelId = 1;
InputStream inputStream = apiClient.getCaptions(revAiJob.getJobId(), RevAiCaptionType.VTT, channelId);

Streaming Audio

In order to stream audio, you will need to setup a streaming client and the content type for the audio you will be sending.

StreamContentType streamContentType = new StreamContentType();
    streamContentType.setContentType("audio/x-raw");
    streamContentType.setLayout("interleaved");
    streamContentType.setFormat("S16LE");
    streamContentType.setRate(16000);
    streamContentType.setChannels(1);

StreamingClient streamingClient = new StreamingClient("Your Access Token");

You will need to create Listener that implements the RevAiWebSocketListener in order to handle WebSocket events.

public class Listener implements RevAiWebSocketListener {

    @Override
    public void onConnected(ConnectedMessage message) {
        System.out.println("On Connected: " + message);
    }

    @Override
    public void onHypothesis(Hypothesis hypothesis) {
        System.out.println("On Hypothesis: " + hypothesis);
    }

    @Override
    public void onError(Throwable t, Response response) {
        System.out.println("On Error: " + response.toString());
    }

    @Override
    public void onClose(int code, String reason) {
        System.out.println("On Close: [" + code + "] " + reason);
    }

    @Override
    public void onOpen(Response response) {
        System.out.println("On Open: " + response.toString());
    }
}

Now you will be able to connect and start the streaming session by calling the streamingClient.connect() method and passing in the Listener! You can supply an optional SessionConfig object, containing metadata, filter_profanity, remove_disfluencies, and delete_after_seconds as optional parameters, to the function in order to provide additional information for that session.

Listener listener = new Listener();

SessionConfig sessionConfig = new SessionConfig();
sessionConfig.setMetaData("My first job");
sessionConfig.setFilterProfanity(true);

streamingClient.connect(clientListener, streamContentType, sessionConfig);

You can stream data over the WebSocket in the form of a ByteString using the streamingClient.sendAudioData() method.

streamingClient.sendAudioData(ByteString);

The streaming connection will close when you call the method streamingClient.close() or if you go 15 seconds without sending any audio data.

Custom Vocabulary

You can submit any custom vocabularies independently through the CustomVocabulariesClient. Once the custom vocabulary has been submitted and processed, it is ready to be used in any async or streaming job.

Below you can see an example of how to create, submit, delete, check on the status and view the other associated information of your custom vocabulary.

// Initialize your client with your Rev AI access token
String accessToken = "Your Access Token";
CustomVocabulariesClient customVocabulariesClient = new CustomVocabulariesClient(accessToken);

// Construct a CustomVocabulary object using your desired phrases
List<String> phrases = Arrays.asList("Patrick Henry Winston", "Robert C Berwick", "Noam Chomsky");
CustomVocabulary customVocabulary = new CustomVocabulary(phrases);

// Submit the CustomVocabulary
CustomVocabularyInformation submittedVocabularyInformation = customVocabularyClient.submitCustomVocabularies(Collections.singletonList(customVocabulary));

// View the custom vocabulary information
CustomVocabularyInformation retrievedVocabularyInformation = customVocabularyClient.getCustomVocabularyInformation(submittedVocabulary.getId());

// View list of custom vocabularies information
List<CustomVocabularyInformation> customVocabulariesInformation = customVocabularyClient.getListOfCustomVocabularyInformation();

// Delete a custom vocabulary by id
customVocabularyClient.deleteCustomVocabulary(retrievedVocabularyInformation.getId());

For Rev AI Java SDK Developers

Before contributing to the project please install the following

• IntelliJ IDE
• google-java-format plugin

Before opening a pull-request

• go to Settings > Plugins and install google-java-format.
• then Settings > google-java-format Settings and click enable option.
• please run the Code > Reformat Code option in any classes that were touched to ensure the code is formatted correctly. You can also right click on src folder and run Reformat Code.

Run mvn package to build the code, run the unit tests and create the SDK jar.

Run mvn verify to also run integration tests. They require the REVAI_ACCESS_TOKEN environment variable to be set to a valid Rev AI access token.

To save the REVAI_ACCESS_TOKEN to be available for Integration tests

• go to Run > Edit Configurations and add a new JUnit configuration if none exists yet.
• for the new JUnit configuration, go to Environmental Variables and click on the browse option.
• click + and add TOKEN under name and REVAI_ACCESS_TOKEN under value.