PyThaiTTS

Open Source Thai Text-to-speech library in Python

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License: Apache-2.0 License

Install

Install by pip:

pip install pythaitts

Usage

Basic Usage

from pythaitts import TTS

tts = TTS()
file = tts.tts("ภาษาไทย ง่าย มาก มาก", filename="cat.wav") # It will get wav file path.
wave = tts.tts("ภาษาไทย ง่าย มาก มาก",return_type="waveform") # It will get waveform.

Using Different TTS Models

PyThaiTTS supports multiple TTS models. You can specify which model to use:

from pythaitts import TTS

# Use FastThaiG2P (default) (default voice: thai_som)
# FastThaiG2P Sample Rate is 24000 Hz
tts = TTS(pretrained="fastthaig2p")
file = tts.tts("สวัสดีครับ", speaker_idx="thai_som", filename="output.wav")

# Use Lunarlist ONNX
# Sample Rate is 22050 Hz
tts = TTS(pretrained="lunarlist_onnx")
file = tts.tts("ภาษาไทย ง่าย มาก", filename="output.wav")

# Use VachanaTTS (default voices: th_f_1, th_m_1, th_f_2, th_m_2)
# Sample Rate is 22050 Hz
tts = TTS(pretrained="vachana")
file = tts.tts("สวัสดีครับ", speaker_idx="th_f_1", filename="output.wav")

# Use KhanomTan
# Sample Rate is 16000 Hz
tts = TTS(pretrained="khanomtan")
file = tts.tts("ภาษาไทย", speaker_idx="Linda", filename="output.wav")

Real-time / Streaming TTS (FastThaiG2P)

PyThaiTTS supports low-latency, real-time streaming speech synthesis with FastThaiG2P, making it ideal for conversational voice agents and LLM streaming:

1. Streaming Audio from Text

Synthesize chunk-by-chunk in real time:

from pythaitts import TTS

tts = TTS(pretrained="fastthaig2p")

# Stream audio chunks as 24kHz float32 NumPy arrays
for audio_chunk in tts.stream("สวัสดีครับ ยินดีต้อนรับสู่ระบบเรียลไทม์ทีทีเอส"):
    print(f"Audio chunk shape: {audio_chunk.shape}")

# Stream raw 16-bit PCM bytes (for WebSockets or PyAudio)
for pcm_bytes in tts.stream("สวัสดีครับ", return_type="bytes"):
    # send over websocket or write to audio stream
    pass

2. Streaming from an LLM Token Stream

Feed tokens directly from an LLM or generator into tts.stream():

from pythaitts import TTS

tts = TTS()

def token_stream():
    tokens = ["สวัสดี", "ครับ", " ", "นี่", "คือ", "การ", "สตรีม", "มิ่ง"]
    for tok in tokens:
        yield tok

for audio_chunk in tts.stream(token_stream()):
    # Process or play chunk with low latency
    pass

3. Integration with the RealtimeTTS Library

You can use FastThaiG2P as an engine with KoljaB/RealtimeTTS:

pip install pythaitts[realtime]

from RealtimeTTS import TextToAudioStream
from pythaitts.realtime import FastThaiG2PEngine

engine = FastThaiG2PEngine()
stream = TextToAudioStream(engine)
stream.feed("สวัสดีครับ วันนี้อากาศดีมาก")
stream.play()

Text Preprocessing

PyThaiTTS includes automatic text preprocessing to improve TTS quality:

• Number to Thai text conversion: Converts digits (e.g., "123") to Thai text (e.g., "หนึ่งร้อยยี่สิบสาม")
• Mai yamok (ๆ) expansion: Expands the Thai repetition character (e.g., "ดีๆ" becomes "ดีดี")

Preprocessing is enabled by default:

from pythaitts import TTS

tts = TTS()
# Automatic preprocessing: "มี 5 คนๆ" becomes "มี ห้า คนคน"
file = tts.tts("มี 5 คนๆ", filename="output.wav")

You can disable preprocessing if needed:

file = tts.tts("มี 5 คนๆ", preprocess=False, filename="output.wav")

You can also use preprocessing functions directly:

from pythaitts import num_to_thai, expand_maiyamok, preprocess_text

# Convert numbers to Thai text
print(num_to_thai("123"))  # Output: หนึ่งร้อยยี่สิบสาม

# Expand mai yamok
print(expand_maiyamok("ดีๆ"))  # Output: ดีดี

# Full preprocessing
print(preprocess_text("มี 5 คนๆ"))  # Output: มี ห้า คนคน

You can see more at https://pythainlp.github.io/PyThaiTTS/.