The popularity of smart home devices like Amazon Echo or Google Home has increased a lot over the past years. All this traction improved the text to speech experience to a point where it is difficult to tell that you are actually not talking to a real person. Not only does this happen in English, but also other supported languages such as French or Japanese, thus exacerbating the problem.
Amazon Polly is an AWS service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice. This service lets you transcribe any text to a high-quality natural sounding voice in a very simple way without overspending. Amazon Polly’s pay-as-you-go pricing, low cost per character converted, and unlimited replays make it a cost-effective way to give your applications a voice. Duolingo and telephony companies are powered by Amazon Polly since the speech experience is very realistic.
Up next, I will explain how Amazon Polly and Twilio can be used to build a speech-enabled application. The application will make phone calls and use Amazon Polly to talk with the callee in a realistic way. Twilio is the leader in the cloud communications platform world and using their Java SDK is very simple and powerful for developers.
Twilio
Twilio and Amazon Polly integration
Twilio has its own speech synthesis but it is language limited and not very life-like. A workaround is to use Amazon Polly to generate mp3 files and have them available on Amazon S3 for consumption by Twilio. The good news is that Twilio recently added an Amazon Polly integration so it can be directly used without having to manage your own files. This integration makes the setup easy and everything can be configured in the Twilio console. You can follow the instructions from the Twilio's blog post to configure the text-to-speech provider to use Amazon Polly.
TwiML
TwiML (the Twilio Markup Language) is a set of instructions you can use to tell Twilio what to do when making a call or sending a SMS. For now, the application will just call a number and say custom text with a configurable voice. TwiML verbs are actions to take on a given call, cool things can be done like recording the callee's voice or collecting typed digits. A list of all TwiML usable verbs can be found at the documentation page about TwiML.
The TwiML to say Hello from Twilio and Amazon Polly with the Amazon Polly Joanna voice looks like below:
<?xml version="1.0" encoding="UTF-8"?>
<Response>
<Say voice="Polly.Joanna">Hello from Twilio and Amazon Polly</Say>
</Response>
Twilio requires a TwiML to initiate a call and the file must be accessible from a regular URL. To fulfil this requirement, the application will simply upload the generated TwiML to Amazon S3 with a public read access. A different way would be to have a simple GET endpoint in the application that returns the TwiML.
Speech-Enabled Application
JHipster Generation
I decided to use JHipster to generate my speech-enabled application since I want a complete and modern Web app. JHipster uses Spring Boot for the back-end and I decided to use Vue.js for the front-end. You can read my previous blog post about JHipster and Vue.js for more details.
This .yo-rc.json can be used in case you want to generate the same application referenced in this article. The file is placed in the application directory and then running jhipster --blueprint vuejs will generate the application without asking any questions.
Entities generation
The entity VoiceCall will be used to keep track of the calls made by the application. Here is entities.jdl and the command jhipster import-jdl entities.jdl will generate everything for you.
entity VoiceCall {
number String required, // Phone number to call
message String required, // Message to be converted to speech
voice Voice required, // Amazon Polly's voice
twiml String, // TwiML used by Twilio
date ZonedDateTime // Date of the call
}
enum Voice {
JOANNA, MATTHEW, CELINE, MATHIEU // 4 voices are used but 50 are available
}
Create realistic calls with Twilio
The Twilio and AWS clients need to be initialized with working credentials so they can be later used:
private static final String BUCKET = "MY_BUCKET";
private static final String TWILIO_NUMBER = "NUMBER";
private final S3Client s3;
public VoiceCallResource(VoiceCallRepository voiceCallRepository) {
this.voiceCallRepository = voiceCallRepository;
// Initialize Twilio
Twilio.init("USERNAME", "PASSWORD");
// Create S3 client using default credential profile
s3 = S3Client.builder().region(Region.US_EAST_1).credentialsProvider(ProfileCredentialsProvider.create()).build();
}
You can get your Twilio's credentials from the console. I used the AWS CLI with the command aws configure to create a default credential profile.
The last step is to update the method createVoiceCall so Twilio can create a call when a VoiceCall is created by the user:
@PostMapping("/voice-calls")
public ResponseEntity<VoiceCall> createVoiceCall(@Valid @RequestBody VoiceCall voiceCall) throws URISyntaxException {
log.debug("REST request to save VoiceCall : {}", voiceCall);
if (voiceCall.getId() != null) {
throw new BadRequestAlertException("A new voiceCall cannot already have an ID", ENTITY_NAME, "idexists");
}
// Generate TwiML
Say say = new Say.Builder(voiceCall.getMessage()).voice(Say.Voice.valueOf("POLLY_" + voiceCall.getVoice().name())).build();
VoiceResponse twiml = new VoiceResponse.Builder()
.say(say)
.pause(new Pause.Builder().length(1).build())
.build();
// Update VoiceCall
voiceCall.twiml(twiml.toXml())
.date(ZonedDateTime.now());
VoiceCall result = voiceCallRepository.save(voiceCall);
// Save TwiML to S3 with public read
PutObjectRequest putRequest = PutObjectRequest.builder()
.bucket(BUCKET)
.key(result.getId() + ".xml")
.contentType("text/xml")
.acl(ObjectCannedACL.PUBLIC_READ)
.build();
s3.putObject(putRequest, software.amazon.awssdk.core.sync.RequestBody.fromString(result.getTwiml()));
// Make call using Twilio
String twimlUri = "https://s3.amazonaws.com/" + putRequest.bucket() + "/" + putRequest.key();
Call call = Call.creator(new PhoneNumber(voiceCall.getNumber()), new PhoneNumber(TWILIO_NUMBER), new URI(twimlUri))
.setMethod(HttpMethod.GET)
.create();
log.debug("CALL SID : {}", call.getSid());
return ResponseEntity.created(new URI("/api/voice-calls/" + result.getId()))
.headers(HeaderUtil.createEntityCreationAlert(ENTITY_NAME, result.getId().toString()))
.body(result);
}
Here is the workflow:
- Generate a TwiML with user's message and voice
- Update VoiceCall with TwiML and current date
- Save TwiML to S3
- Call user's number with Twilio using the TwiML from S3
- Return created VoiceCall with a HTTP 201
To keep this post simple, I decided to upload the TwiML to S3 with a public read access. I recommend using a presigned URL, especially for an application going to production.
Testing
To test that everything is working fine, the application must be first started with the command ./mvnw. You can then browse to http://localhost:8080/#/entity/voice-call/new to create a VoiceCall (don't forget the +1 in front of your number).
If you don't receive the call after saving, the Twilio's calls log keeps track of all the calls and can be used for troubleshooting.
Conclusion
Building a speech-enabled application might sound difficult but with the help of Twilio and AWS it is actually very easy. The developer experience is also very good since Twilio provides a SDK in 6 languages (Node, C#, PHP, Ruby, Python and Java) and they also provide a REST API. Amazon Polly gives you a large panel of realistic voices to make your application fully international by supporting multiple languages.
The code used in this blog post is available at this GitHub repository in case you want to clone a working example.
