> For the complete documentation index, see [llms.txt](https://langtech-bsc.gitbook.io/aina-kit/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://langtech-bsc.gitbook.io/aina-kit/aina-hack/text-to-speech/matxa-multispeaker-catalan-central-endpoint.md).

# Matxa Multispeaker Catalan Central Endpoint

**Input parameters**

| Parameter     | Description                                                                                         | Type   | Options/Range                   | Recommended Values |
| ------------- | --------------------------------------------------------------------------------------------------- | ------ | ------------------------------- | ------------------ |
| text          | Input text to be converted to speech                                                                | string | Any text input                  | N/A                |
| voice         | Speaker ID for voice output                                                                         | int    | 47 different speakers available | N/A                |
| temperature   | Controls sampling variance during inference. Lower values yield higher quality but less variability | float  | 0.2 to 0.67                     | 0.2 to 0.67        |
| length\_scale | Related to speech speed. Higher values make the speech slower, while lower values make it faster    | float  | 0.75 to 0.9                     | 0.75 to 0.9        |

Each integer value is associated with one of the speakers you see in the list below. All names starting with “caf\_XXXXX” (female) and “cam\_XXXXX” (male) belong to speakers in the [OpenSLR69](https://huggingface.co/datasets/projecte-aina/openslr-slr69-ca-trimmed-denoised) dataset and short Catalan names in the [festcat](https://huggingface.co/datasets/projecte-aina/festcat_trimmed_denoisedfestcat) dataset.

```json
"cam_03115": 0,
  "caf_04247": 1,
  "caf_05450": 2,
  "cam_08935": 3,
  "caf_09901": 4,
  "ona": 5,
  "pol": 6,
  "cam_02689": 7,
  "caf_06042": 8,
  "jan": 9,
  "caf_08106": 10,
  "cam_04910": 11,
  "cam_08664": 12,
  "caf_07803": 13,
  "cam_06582": 14,
  "caf_06311": 15,
  "caf_07245": 16,
  "cam_06279": 17,
  "caf_09598": 18,
  "caf_09796": 19,
  "eva": 20,
  "cam_00762": 21,
  "caf_09204": 22,
  "caf_03944": 23,
  "caf_05147": 24,
  "uri": 25,
  "mar": 26,
  "cam_00459": 27,
  "teo": 28,
  "caf_03655": 29,
  "bet": 30,
  "cam_06705": 31,
  "caf_05739": 32,
  "caf_06008": 33,
  "cam_04484": 34,
  "cam_03386": 35,
  "cam_08967": 36,
  "caf_06942": 37,
  "cam_07140": 38,
  "pau": 39,
  "caf_08001": 40,
  "pep": 41,
  "cam_04787": 42,
  "eli": 43,
  "caf_01591": 44,
  "caf_02452": 45,
  "cam_02992": 46
```

### Code examples

**Python**

{% code title="example.py" %}

```python
import requests

API_URL = "https://x6g02u4lkf25gcjo.us-east-1.aws.endpoints.huggingface.cloud/api/tts"
headers = {
   "Authorization": "Bearer <hf_token>",
}

def query(text):
   data = {"text": text, "voice": 20}
   return requests.post(API_URL, headers=headers, json=data)

response = query("Bon dia")
with open("output.wav", "wb") as f:
   f.write(response.content)
```

{% endcode %}

**Curl**

Please take into account the apostrophes. An effective way is to create a temporary JSON file to pass text and input parameters for inference.

{% code title="bash" %}

```bash
printf '%s' '{
  "text": "L'\''Aina ha preparat aquest model de síntesi de veu.",
  "voice": 39,
  "type": "text"
}' > data.json

curl -X POST https://x6g02u4lkf25gcjo.us-east-1.aws.endpoints.huggingface.cloud/api/tts -H "Content-Type: application/json" -H "Authorization: Bearer <hf_token>" -d @data.json | play -t wav -

rm data.json// Some code
```

{% endcode %}

**Javascript**

Executed with Node.js. Install NPM (Node Package Manager) and with NPM install fetch-node library.

{% code title="example.js" %}

```javascript
const fetch = require("node-fetch");
const fs = require("fs");

// Define the API URL and headers
const API_URL = "https://x6g02u4lkf25gcjo.us-east-1.aws.endpoints.huggingface.cloud/api/tts";
const headers = {
    "Authorization": "Bearer <hf_token>",
    "Content-Type": "application/json"
};

// Function to send the request
async function query(text) {
    const data = {
        text: text,
        voice: 20,
    };

    try {
        // POST request
        const response = await fetch(API_URL, {
            method: "POST",
            headers: headers,
            body: JSON.stringify(data)
        });

        // Check the response
        if (!response.ok) {
            throw new Error(`Error: ${response.status} ${response.statusText}`);
        }

        // Convert the response to a buffer
        const buffer = await response.buffer();

        // Write the buffer to an output file
        fs.writeFile("output.wav", buffer, (err) => {
            if (err) {
                console.error("Error saving the file:", err);
            } else {
                console.log("File saved as output.wav");
            }
        });

        
    } catch (error) {
        console.error("Error making request:", error);
    }
}

// Example usage
query("Bon dia.");

```

{% endcode %}