Deepgram API Playground

Try this feature out in our API Playground.

\
 Text to Speech Request

This guide will walk you through how to turn text into speech with Deepgram's text-to-speech REST API.

:::callout{intent="info"}
Before you start, you'll need to follow the steps in the [Make Your First API Request](/guides/guides-fundamentals-make-your-first-api-request) guide to obtain a Deepgram API key, and configure your environment if you are choosing to use a Deepgram SDK.
:::

## CURL

Next, try it with CURL. Add your own API key where it says `YOUR_DEEPGRAM_API_KEY` and then run the following example in a terminal or your favorite API client.

**`cURL`**

```bash cURL
curl --request POST \
     --header "Content-Type: application/json" \
     --header "Authorization: Token DEEPGRAM_API_KEY" \
     --output your_output_file.mp3 \
     --write-out "Time-to-First-Byte: %{time_starttransfer}s Time-to-Last-Byte: %{time_total}s\n" \
     --data '{"text":"Hello, how can I help you today?"}' \
     --url "https://api.deepgram.com/v1/speak?model=aura-2-thalia-en"
```

This will result in an MP3 audio file being streamed back to you by Deepgram. You can play the audio as soon as you receive the first byte, or you can wait until the entire MP3 file has arrived.

The audio file will contain the voice of the selected model saying the words that you sent in your request.

:::callout{intent="info"}
If you do not specify a `model`, the default voice model `aura-asteria-en` will be used. You can find all of our available voices [here](/guides/aura-tts-models).
:::

### Send Error Messages to Terminal

If your request results in an error, the error message can be seen by opening the output audio file in a text editor.

To see the error message in your terminal, add this to your CURL request:

**`cURL`**

```bash cURL
--fail-with-body \
--silent \
|| (jq . your_output_file.mp3 && rm your_output_file.mp3)
```

This example will capture the error message using the [JQ](https://jqlang.org/) JSON processor library and remove the output file `tts.mp3` automatically.

**`cURL`**

```bash cURL
curl --request POST \
     --header "Content-Type: application/json" \
     --header "Authorization: Token DEEPGRAM_API_KEY" \
     --output your_output_file.mp3 \
     --write-out "Time-to-First-Byte: %{time_starttransfer}s Time-to-Last-Byte: %{time_total}s\n" \
     --data '{"text":"Hello, how can I help you today?"}' \
     --url 'https://api.deepgram.com/v1/speak?model=testing_error' \
     --fail-with-body \
     --silent \
     || (jq . your_output_file.mp3 && rm your_output_file.mp3)
```

## SDKs

Deepgram has several SDKs that can make it easier to use the API. Follow these steps to use the SDK of your choice to make a Deepgram TTS request.

### Install the SDK

Open your terminal, navigate to the location on your drive where you want to create your project, and install the Deepgram SDK.

:::code-group
```shell title="JavaScript"
# Install the Deepgram JS SDK
# https://github.com/deepgram/deepgram-js-sdk

npm install @deepgram/sdk
```

```shell title="Python"
# Install the Deepgram Python SDK
# https://github.com/deepgram/deepgram-python-sdk

pip install deepgram-sdk
```

```shell title="Go"
# Install the Deepgram Go SDK
# https://github.com/deepgram/deepgram-go-sdk

go get github.com/deepgram/deepgram-go-sdk
```

```shell title="C#"
dotnet add package Deepgram
```

```shell title="Java"
# Install the Deepgram Java SDK
# https://github.com/deepgram/deepgram-java-sdk

# Maven — add to pom.xml:
# <dependency>
#   <groupId>com.deepgram</groupId>
#   <artifactId>deepgram-java-sdk</artifactId>
#   <version>0.10.0</version>
# </dependency>

# Gradle — add to build.gradle:
# implementation 'com.deepgram:deepgram-java-sdk:0.10.0'
```
:::

### Add Dependencies

:::code-group
```shell title="JavaScript"
# Install dotenv to protect your api key

npm install dotenv
```

```shell title="Python"
# Install python-dotenv to protect your api key

pip install python-dotenv
```

```shell title="Go"
# Importing the Deepgram Go SDK should pull in all dependencies required
```

```shell title="C#"
# Importing the Deepgram Go SDK should pull in all dependencies required
```
:::

### Make the Request with the SDK

:::code-group
```javascript title="JavaScript"
const { DeepgramClient } = require("@deepgram/sdk");
const fs = require("fs");

// STEP 1: Create a Deepgram client with your API key
const deepgram = new DeepgramClient({ apiKey: process.env.DEEPGRAM_API_KEY });

const text = "Hello, how can I help you today?";

const getAudio = async () => {
  // STEP 2: Make a request and configure the request with options (such as model choice, audio configuration, etc.)
  const response = await deepgram.speak.v1.audio.generate({
    text,
    model: "aura-2-thalia-en",
    encoding: "linear16",
    container: "wav",
  });

  // STEP 3: Get the audio stream from the response
  const stream = response.stream();
  if (stream) {
    // STEP 4: Convert the stream to an audio buffer
    const buffer = await getAudioBuffer(stream);
    // STEP 5: Write the audio buffer to a file
    fs.writeFile("output.wav", buffer, (err) => {
      if (err) {
        console.error("Error writing audio to file:", err);
      } else {
        console.log("Audio file written to output.wav");
      }
    });
  } else {
    console.error("Error generating audio:", stream);
  }

};

// helper function to convert stream to audio buffer
const getAudioBuffer = async (response) => {
  const reader = response.getReader();
  const chunks = [];

  while (true) {
    const { done, value } = await reader.read();
    if (done) break;

    chunks.push(value);
  }

  const dataArray = chunks.reduce(
    (acc, chunk) => Uint8Array.from([...acc, ...chunk]),
    new Uint8Array(0)
  );

  return Buffer.from(dataArray.buffer);
};

getAudio();
```

```python title="Python"
# For more Python SDK migration guides, visit:
# https://github.com/deepgram/deepgram-python-sdk/tree/main/docs

import os
import logging

from deepgram import (
    DeepgramClient,
)

def main():
    try:
        # STEP 1 Create a Deepgram client using the API key from environment variables
        deepgram = DeepgramClient()

        # STEP 2 Call the generate method on the speak property
        response = deepgram.speak.v1.audio.generate(
            text="Hello world!",
            model="aura-2-thalia-en"
        )

        # Save the audio file
        with open("test.mp3", "wb") as audio_file:
            for chunk in response:
                audio_file.write(chunk)

        print(f"Audio saved to test.mp3")

    except Exception as e:
        print(f"Exception: {e}")

if __name__ == "__main__":
    main()
```

```go title="Go"
package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	prettyjson "github.com/hokaccha/go-prettyjson"

	speak "github.com/deepgram/deepgram-go-sdk/pkg/api/speak/v1"
	interfaces "github.com/deepgram/deepgram-go-sdk/pkg/client/interfaces"
	client "github.com/deepgram/deepgram-go-sdk/pkg/client/speak"
)

const (
	textToSpeech string = "Hello, how can I help you today?"
	filePath     string = "./output.wav"
)

func main() {
	// STEP 1: init Deepgram client library
	client.InitWithDefault()

	// STEP 2: define context to manage the lifecycle of the request
	ctx := context.Background()

	// STEP 3: define options for the request
	options := interfaces.SpeakOptions{
		Model:     "aura-2-thalia-en",
		Encoding:  "linear16",
		Container: "wav",
	}

	// STEP 4: create a Deepgram client using default settings
	// NOTE: you can set your API KEY in your bash profile by typing the following line in your shell:
	// export DEEPGRAM_API_KEY = "YOUR_DEEPGRAM_API_KEY"
	c := client.NewWithDefaults()
	dg := speak.New(c)

	// STEP 5: send/process file to Deepgram
	res, err := dg.ToSave(ctx, filePath, textToSpeech, options)
	if err != nil {
		fmt.Printf("FromStream failed. Err: %v\n", err)
		os.Exit(1)
	}

	// STEP 6: get the JSON response
	data, err := json.Marshal(res)
	if err != nil {
		fmt.Printf("json.Marshal failed. Err: %v\n", err)
		os.Exit(1)
	}

	// STEP 8: make the JSON pretty
	prettyJson, err := prettyjson.Format(data)
	if err != nil {
		fmt.Printf("prettyjson.Marshal failed. Err: %v\n", err)
		os.Exit(1)
	}
	fmt.Printf("\n\nResult:\n%s\n\n", prettyJson)
}
```

```csharp title="C#"
using Deepgram.Models.Speak.v1.REST;

namespace SampleApp
{
    class Program
    {
        static async Task Main(string[] args)
        {
            // Initialize Library with default logging
            // Normal logging is "Info" level
            Library.Initialize();

            // use the client factory with a API Key set with the "DEEPGRAM_API_KEY" environment variable
            var deepgramClient = ClientFactory.CreateSpeakRESTClient();

            var response = await deepgramClient.ToFile(
                new TextSource("Hello World!"),
                "test.mp3",
                new SpeakSchema()
                {
                    Model = "aura-2-thalia-en",
                });

            //Console.WriteLine(response);
            Console.WriteLine(response);
            Console.ReadKey();

            // Teardown Library
            Library.Terminate();
        }
    }
}
```

```java title="Java"
// Main.java (Java example)
// https://github.com/deepgram/deepgram-java-sdk

import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.StandardCopyOption;
import com.deepgram.DeepgramClient;
import com.deepgram.resources.speak.v1.audio.requests.SpeakV1Request;

public class Main {
    public static void main(String[] args) throws Exception {
        // Create a client using DEEPGRAM_API_KEY from the environment
        DeepgramClient client = DeepgramClient.builder().build();

        // Generate speech audio
        InputStream audioStream = client.speak().v1().audio().generate(
            SpeakV1Request.builder()
                .text("Hello, how can I help you today?")
                .build()
        );

        // Save to file
        Files.copy(audioStream, Path.of("output.mp3"), StandardCopyOption.REPLACE_EXISTING);
        System.out.println("Audio saved to output.mp3");
    }
}
```
:::

:::callout{intent="info"}
To learn more about how you can customize the audio file to meet the needs of your use case, take a look at this [Audio Format Combinations](/guides/media-output-settings-index#audio-format-combinations) table.
:::

## Non-SDK Code Examples

If you would like to try out making a Deepgram speech-to-text request in a specific language (but not using Deepgram's SDKs), we offer a library of code-samples in this [Github repo](https://github.com/deepgram-devs/code-samples). However, we recommend first trying out our SDKs, which we presented in the previous section.

## Results

Upon successful processing of the request, you will receive an audio file containing the synthesized text-to-speech output, along with response headers providing additional information.

:::callout{intent="info"}
The audio file is streamed back to you, so you may begin playback as soon as the first byte arrives. Read the guide [Streaming Audio Outputs](/guides/results-processing-2-streaming-the-audio-output) to learn how to begin playing the stream immediately versus waiting for the entire file to arrive.
:::

### Example Response Headers

**`http`**

```text http
HTTP/1.1 200 OK
< content-type: audio/mpeg
< dg-model-name: aura-2-thalia-en
< dg-model-uuid: e4979ab0-8475-4901-9d66-0a562a4949bb
< dg-char-count: 32
< dg-request-id: bf6fc5c7-8f84-479f-b70a-602cf5bf18f3
< transfer-encoding: chunked
< date: Thu, 29 Feb 2024 19:20:48 GMT
```

:::callout{intent="info"}
To see these response headers when making a CURL request, add `-v` or `--verbose` to your request.
:::

This includes:

- `content-type`: Specifies the media type of the resource, in this case, `audio/mpeg`, indicating the format of the audio file returned.
- `dg-request-id`: A unique identifier for the request, useful for debugging and tracking purposes.
- `dg-model-uuid`: The unique identifier of the model that processed the request.
- `dg-char-count`: Indicates the number of characters that were in the input text for the text-to-speech process.
- `dg-model-name`: The name of the model used to process the request.
- `transfer-encoding`: Specifies the form of encoding used to safely transfer the payload to the recipient.
- `date`: The date and time the response was sent.

## Limits

Keep these limits in mind when making a Deepgram text-to-speech request.

### Input Text Limit

Sending a request with a text payload longer than the maximum number of characters can result in a [**413: Input Text Exceeds Character Limits**](/guides/self-hosted-deployments-2-docs-errors#413-input-text-exceeded-character-limit) error, and the audio file will not be created.

| Model          | Max Characters |
| -------------- | -------------- |
| Aura-2, Aura-1 | 2000           |

### Unprocessable Content

A [**422: Unprocessable Content**](/guides/self-hosted-deployments-2-docs-errors#422-unprocessable-content) error can be returned if the client fails to send the request successfully.

### Rate Limits

:::callout{intent="info"}
For information on Deepgram's Concurrency Rate Limits, refer to our [API Rate Limits Documentation](/guides/self-hosted-deployments-2-reference-api-rate-limits).
:::

#### Handling Rate Limits

If the number of in-progress requests for a project meets or exceeds the rate limit, new requests will receive a **429: Too Many Requests** error.

:::callout{intent="info"}
For suggestions on handling Concurrency Rate Limits, refer to our [Working with Concurrency Rate Limits Documentation](/guides/guides-docs-working-with-concurrency-rate-limits) guide.
:::

## What's Next?

Now that you've transformed text into speech with Deepgram's API, enhance your knowledge by exploring the following areas.

### Template Apps

- Clone and run one of our [Template Apps](/guides/aura-tts-rest-template-apps) to see a full application with a frontend UI and a backend server sending text to Deepgram to be converted into audio.

### Read the Feature Guides

Deepgram's features help you to customize your request to produce the output that works best for your use case.

- [Media Output Settings](/guides/media-output-settings-index): Learn how to customize the audio file that is returned.
- [Callback](/guides/results-processing-2-tts-callback): Discover how to provide a callback url, so that your audio can be processed asynchronously.
- [Feature Overview](/guides/aura-tts-feature-overview): Review the list of features available for pre-recorded speech-to-text. Then, dive into individual guides for more details.

### Try the Conversational AI Demo

- The purpose of[ this demo](https://aura-tts-demo.deepgram.com/) is to showcase how you can build a Conversational AI application that engages users in natural language interactions, mimicking human conversation through natural language processing using Deepgram and [OpenAI ChatGPT.](https://openai.com/chatgpt)

### Watch This Video

- Watch this [video](https://www.youtube.com/watch?v=J2sbC8X5Pp8) to learn how you can use Deepgram Aura with [Groq](https://groq.com/) to build a blazing fast Conversational AI application.

***

## Related pages

- [Feature Overview](./aura-tts-feature-overview.md)
- [Template Apps](./aura-tts-rest-template-apps.md)

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