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Realtime TTS API

A dedicated WebSocket endpoint for real-time text-to-speech synthesis. Send text incrementally — from an LLM token stream or user input — and receive synthesized audio as base64-encoded chunks with minimal latency.

Palabra API client​

Consider using the Palabra API Python client and checking the code example with it.

Connection​

Create an API Key on the Palabra API Keys page. Connect to the endpoint below, passing your API Key as the token query parameter (or in the Authorization header). The server validates the key and creates a streaming session for the lifetime of the connection automatically.

wss://stream.palabra.ai/tts-api/v1/text-to-speech/stream?token={API_KEY} - Europe
wss://stream.us.palabra.ai/tts-api/v1/text-to-speech/stream?token={API_KEY} - United States

The connection is rate-limited to 20 new connections per minute per token.

TTS Session lifecycle​

  1. Connect to the WebSocket endpoint
  2. Send an init message to establish voice and output settings
  3. Send text messages — each up to 1024 characters; mark the last chunk of each sentence with is_eos: true
  4. Receive audio_chunk messages with base64-encoded audio as chunks arrive
  5. Send cancel at any time to stop the current synthesis

The session persists until you disconnect. Settings from init apply to the entire session and can be overridden in individual text messages.


Supported TTS Languages​

The table below lists the language codes accepted by the language field of the init message. Codes are lowercase.

CodeLanguage
enEnglish (generic)
en-usEnglish (US)
en-gbEnglish (UK)
deGerman
esSpanish
es-euSpanish (European)
es-laSpanish (Latin American)
frFrench
fr-euFrench (European)
fr-caFrench (Canadian)
hiHindi
itItalian
nlDutch
ptPortuguese
pt-euPortuguese (European)
pt-laPortuguese (Latin American)
ruRussian
koKorean
csCzech
fiFinnish
idIndonesian
plPolish
roRomanian
skSlovak
svSwedish
trTurkish

Client → Server Messages​

init​

Must be sent once, immediately after connecting.

{
"type": "init",
"language": "en",
"model": "auto",
"voice_options": {
"voice_id": "default_low",
"speed": 1.0,
"deaccent_strength": 1.0
},
"output": {
"format": "pcm",
"sample_rate": 24000
}
}
FieldTypeRequiredDefaultDescription
languagestring✓—BCP-47 language code, e.g. en, ru, de, fr.
modelstring—autoTTS model ID. Use auto to select the best model for the language.
voice_optionsobject✓—Voice configuration. See fields below.
outputobject——Output audio settings. See fields below.

voice_options​

FieldTypeRequiredDefaultDescription
voice_idstring✓—Voice identifier. Use default_low or default_high for the language default.
speedfloat—1.0Speed multiplier. 1.0 is normal speed. Range: 0.0–2.0.
deaccent_strengthfloat—1.0Reduces foreign accent. Range: 0.0–1.0.

output​

FieldTypeRequiredDefaultDescription
formatstring—mp3Output audio format. One of pcm, mp3, wav.
sample_rateinteger—24000Output sample rate in Hz. Range: 8000–48000.

text​

Send a chunk of text to synthesize. Each message must be 1024 characters or fewer. Send multiple messages to stream longer text — mark the last chunk of each sentence with is_eos: true.

Voice options can be overridden per message — only the fields you supply are changed.

{
"type": "text",
"text": "Hello, how can I help you today?",
"is_eos": true
}
{
"type": "text",
"text": "This part is spoken faster.",
"is_eos": false,
"voice_options": {
"speed": 1.2
}
}
FieldTypeRequiredDefaultDescription
textstring✓—Text to synthesize. Max 1024 characters per message.
generation_idstring——Optional client-supplied ID (4–256 chars). If set, it's returned as generation_id on the resulting audio_chunk messages so you can correlate output with this request. If omitted, the server assigns one.
is_eosboolean—falseEnd of sentence. When true, finalizes speech synthesis for the provided sentence.
voice_optionsobject——Override of session voice options for this and subsequent messages.

cancel​

Stop the current synthesis immediately. The session stays open — you can send new text messages right after.

{
"type": "cancel"
}

Server → Client Messages​

audio_chunk​

Sent as audio is generated. Each message contains a base64-encoded audio chunk in the format specified in init.output.format.

{
"message_type": "audio_chunk",
"data": {
"audio": "Y3VyaW91cyBtaW5kcyB0aGluayBhbGlrZQ==",
"size": 9600,
"generation_id": "1a2b3c4d",
"last_chunk": false,
"chunk_generation_delta": 120,
"audio_len": 0.2
}
}
FieldTypeDescription
data.audiostringBase64-encoded audio data.
data.sizeintegerSize of the decoded audio in bytes.
data.generation_idstringID of the generation this chunk belongs to. Echoes the generation_id you sent in the text message, or a server-assigned value if you didn't. Use it to correlate chunks with a specific request.
data.last_chunkbooleantrue on the final chunk of a generation — synthesis for that sentence is complete. Lets you detect the end without guessing.
data.chunk_generation_deltainteger | nullLatency metric: milliseconds elapsed from the start of the generation to the moment this chunk was produced. null when the backend reports no timing for the chunk — in particular on the final end-of-generation marker (see last_chunk). Informational only.
data.audio_lennumber | nullDuration of this chunk's audio in seconds. Present on every chunk that carries audio; null on the final end-of-generation marker, which carries no audio.

error​

Sent on session-level or synthesis errors.

{
"message_type": "error",
"data": {
"code": "SERVICE_UNAVAILABLE",
"desc": "Speech synthesis timed out. Please try again."
}
}
CodeRetryableDescription
SERVICE_UNAVAILABLE✓Synthesis service issue. Wait and retry.
SERVER_ERROR✗Server-side synthesis failure that is not retryable.
UNKNOWN_ERROR✗Unexpected, unhandled internal error. Contact support if it persists.
BAD_REQUEST✗Incoming message is not valid JSON or not valid UTF-8. The session stays open.
VALIDATION_ERROR✗Invalid message field. See desc for details.
CONFLICT✗Session already initialised. Reconnect to change settings.
SESSION_NOT_FOUND✗Send init before sending text.
UNAUTHORIZED✗API Key or access token missing, invalid, or expired.
RATE_LIMIT_EXCEEDED✓Text-message rate limit exceeded (max 50 messages per second). The session stays open — wait briefly and retry.
Two independent limits
  • Connections — max 20 new connections per minute per token. Exceeding this does not produce a RATE_LIMIT_EXCEEDED message: the server closes the WebSocket with code 1008 (policy violation) and reason Connection rate limit exceeded. Wait before reconnecting.
  • Text messages — max 50 text messages per second. Exceeding this returns an error with code RATE_LIMIT_EXCEEDED and keeps the session open.

Output formats​

FormatDescription
pcmRaw 16-bit signed PCM, little-endian. No container. Best for real-time playback — schedule each chunk immediately as it arrives.
mp3MPEG Layer 3 compressed audio. Collect all chunks and decode together.
wavPCM with RIFF/WAVE container. Collect all chunks and decode together.
Real-time PCM playback

Decode each data.audio as base64 → Uint8Array → Int16Array (little-endian) → Float32Array, create an AudioBuffer and schedule with AudioBufferSourceNode.start(nextTime) — accumulating nextTime += audioBuffer.duration after each chunk for gapless playback.


Example — streaming from an LLM​

This example shows how sentences split into chunks can be streamed to the TTS API. Voice speed is increased mid-stream to demonstrate per-message overrides.

import asyncio, json, base64, websockets

WS_TTS_URL = "wss://stream.palabra.ai/tts-api/v1/text-to-speech/stream"
API_KEY = "<your-api-key>" # create one at https://platform.palabra.ai/api-keys

SENTENCES = [
(
"The sun was setting over the mountains,",
"casting long golden shadows across the valley below.",
),
(
"Birds were returning to their nests,",
"filling the air with their evening songs.",
),
(
"A gentle breeze moved through the tall grass,",
"creating waves that rippled toward the horizon.",
),
]

async def main():
url = f"{WS_TTS_URL}?token={API_KEY}"

async with websockets.connect(url) as ws:
# 1. Initialise the session
await ws.send(json.dumps({
"type": "init",
"language": "en",
"model": "auto",
"voice_options": {
"voice_id": "default_low",
"speed": 1.0,
"deaccent_strength": 1.0,
},
"output": {
"format": "pcm",
"sample_rate": 24000,
}
}))

# 2. Send each sentence chunk by chunk, is_eos=True on the last chunk of each sentence
sent = 0
for i, sentence in enumerate(SENTENCES):
for k, chunk in enumerate(sentence):
msg = {
"type": "text",
"text": chunk,
"is_eos": k == len(sentence) - 1,
}
if k == 0: # override speed only at the start of each sentence
msg["voice_options"] = {"speed": min(0.5 + i / 10, 1.0)}
await ws.send(json.dumps(msg))
sent += 1

# 3. Collect audio until every generation has signalled last_chunk
audio = bytearray()
done = 0
async for raw in ws:
data = json.loads(raw)
if data.get("message_type") == "audio_chunk":
chunk = data["data"]
audio.extend(base64.b64decode(chunk["audio"]))
print(f"Chunk: {chunk['size']} bytes, total: {len(audio)}")
if chunk.get("last_chunk"):
done += 1
if done == sent: # all sentences finished
break
elif data.get("message_type") == "error":
print(f"Error: {data['data']['code']} — {data['data']['desc']}")
break

print(f"Total: {len(audio)} bytes")
with open("output.pcm", "wb") as f:
f.write(audio)
# Play: ffplay -f s16le -ar 24000 -ac 1 output.pcm

asyncio.run(main())