Convert Text-to-Speech (TTS)

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Prerequisites

• Node.js v20 or higher: Download here
• Inworld API key (required): Sign up here or see quickstart guide

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Run the Template

1. Clone the templates repository:
   git clone https://github.com/inworld-ai/inworld-runtime-templates-node
   cd inworld-runtime-templates-node
   
2. Install the Runtime SDK inside the cli directory.
   Yarn

   npm

   yarn add @inworld/runtime
   

   npm install @inworld/runtime
   
3. Set up your Base64 Runtime API key by copying the .env-sample file into a .env file in the cli folder and adding your API key.
   .env

   # Inworld Agent Runtime Base64 API key
   INWORLD_API_KEY=<your_api_key_here>
   
4. Try a different model or voice! You can specify the model using the --modelId parameter and a voice using the --voiceName parameter:
   yarn node-tts "Hello, how are you?" --modelId=inworld-tts-2 --voiceName=Ronald
   

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Understanding the Template

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1) Node Initialization

const ttsNode = new RemoteTTSNode({
  id: 'tts_node',
  speakerId: voiceName,
  modelId,
  sampleRate: SAMPLE_RATE,
  temperature: 1.0,
  speakingRate: 1,
});

• id: A unique identifier for the node
• speakerId: The voice to use for synthesis (see available voices)
• modelId: The TTS model to use for synthesis
• sampleRate: Audio output sample rate
• temperature: Controls randomness in synthesis
• speakingRate: Controls the speed of speech (1.0 is the voice’s natural speed)

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2) Graph initialization

const graph = new GraphBuilder({
  id: 'node_tts_graph',
  apiKey,
  enableRemoteConfig: false,
})
  .addNode(ttsNode)
  .setStartNode(ttsNode)
  .setEndNode(ttsNode)
  .build();

• id: A unique identifier for the graph
• apiKey: Your Inworld API key for authentication
• enableRemoteConfig: Whether to enable remote configuration (set to false for local execution)

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3) Graph execution

const { outputStream } = await graph.start(text);

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4) Response handling

let initialText = '';
let resultCount = 0;
let allAudioData: number[] = [];

for await (const result of outputStream) {
  await result.processResponse({
    TTSOutputStream: async (ttsStream: GraphTypes.TTSOutputStream) => {
      for await (const chunk of ttsStream) {
        if (chunk.text) initialText += chunk.text;
        if (chunk.audio?.data) {
          allAudioData = allAudioData.concat(Array.from(chunk.audio.data));
        }
        resultCount++;
      }
    },
  });
}

console.log(`Result count: ${resultCount}`);
console.log(`Initial text: ${initialText}`);

• TTSOutputStream: Streaming audio responses containing both text and audio data
• chunk.text: The text being synthesized
• chunk.audio.data: The audio data as Float32Array samples

​

5) Audio file creation

const audio = {
  sampleRate: SAMPLE_RATE,
  channelData: [new Float32Array(allAudioData)],
};

const buffer = await wavEncoder.encode(audio);
if (!fs.existsSync(OUTPUT_DIRECTORY)) {
  fs.mkdirSync(OUTPUT_DIRECTORY, { recursive: true });
}

fs.writeFileSync(OUTPUT_PATH, Buffer.from(buffer));

console.log(`Audio saved to ${OUTPUT_PATH}`);