Async Text to Speech Pro V1.0
Integrate
async/tts-pro/v1.0
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/async/tts-pro/v1.0?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/async/tts-pro/v1.0?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie",
},
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/async/tts-pro/v1.0", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "async/tts-pro/v1.0",
"input": {
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
}
}
Call the Async Text to Speech Pro V1.0 model (async/tts-pro/v1.0) through the Doitong API. Docs for agents: https://doitong.com/developers/models/async/tts-pro/v1.0.md
POST https://api.doitong.com/v1/run/async/tts-pro/v1.0?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
}
If the response status is "queued" or "running", poll GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 until it is "succeeded"; the files are in outputs[].url. POST https://api.doitong.com/v1/quote/async/tts-pro/v1.0 with the same body returns the exact price before the run.
This request: $0.001 1 API credit Run it on this page
Your new API key. It is shown only now and is already in the code and in the API key field below. Keep it secret: never put it in code that runs in a browser.
Your first result goes here
Build a request below and run it with your API key. Outputs are copied to our storage, kept forever or 7 days for free.
Build a request
Controls are generated from the model schema. The code and the price update as you change them.
/run/async/tts-pro/v1.0?wait=20
quote → $0.001
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/async/tts-pro/v1.0?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/async/tts-pro/v1.0?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie",
},
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/async/tts-pro/v1.0", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "async/tts-pro/v1.0",
"input": {
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
},
"wait_seconds": 20
}
}
}
Run this request
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About Async Text to Speech Pro V1.0
Converts a `transcript` into speech using a chosen `voice` object. The optional `language` parameter forces synthesis in English, French, Spanish, German, Italian or Portuguese. An `output_format` object configures the audio, and the result includes the audio file, its MIME type and its size in bytes. Suited to voiceovers where you pick a specific voice.
Parameters
transcriptrequired
voicerequired
voice.nameoptional
+84 more
EiraNyraArianLilyPierceKaelaElowenFreyaLennyAlessaPandoraFiaAbbottKaelOrlaSableMarnieSeraVirelLioraRivenElysDreenaRheaVelaNymeraIsoldeLirienZellaAvennaMirelleCaliaLuneaLucanTarianArloJovanNeronZivenDaxOrienLiorEryxTyrenNoxElricVarianZoranMiroDalenRonixJarekNyxieSorenVionaSeleneRachielCorbinAbigailFaithKimberlyDaveGraceAldenRenlyVioletJoelXavierEsmeraldaRobertLilaBrooksLennoxVanessaSimonNyomiJackPenelopeBraydenAbelNellieConnieAndrewLincolnoutput_formatoptional
output_format.containeroptional
output_format.encodingoptional
output_format.sample_rateoptional
output_format.bit_rateoptional
languageoptional
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "async/tts-pro/v1.0",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 1,
"usd": "0.001",
"charged": 1,
"refunded": 0
},
"input": {
"transcript": "Hello from Doitong. This is a short test sentence.",
"voice": {
"name": "Jennie"
}
},
"output": {
"audio": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp3",
"content_type": "audio/mpeg",
"file_name": "0-output.mp3",
"file_size": 1843200
},
"content_type": "audio/mpeg",
"size_bytes": 1
},
"outputs": [
{
"type": "audio",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp3",
"content_type": "audio/mpeg",
"file_size": 1843200,
"duration": 12,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Fields of output
- audio
- object {url, content_type, file_name, file_size}
- content_type
- stringAudio MIME type.
- size_bytes
- integerAudio size measured in bytes.
More models: Text to Speech
For AI agents: this page as Markdown is at https://doitong.com/developers/models/async/tts-pro/v1.0.md. All models and guides: https://doitong.com/developers/llms.txt