Pocket TTS

Lightweight CPU-friendly text-to-speech with voice cloning. No GPU required.

When to Use

Generating speech from text on CPU without GPU
Voice cloning from audio samples
Streaming audio generation (low latency)
Local TTS without API dependencies
Real-time speech synthesis (~6x faster than real-time)

Key Features

100M parameters - Small, efficient model
CPU-optimized - No GPU needed, uses only 2 cores
~6x real-time - Fast generation on modern CPUs
~200ms latency - To first audio chunk (streaming)
Voice cloning - From 3-10s audio samples
24kHz mono WAV - High-quality output
English only - More languages planned

Installation

pip install pocket-tts
# or
uv add pocket-tts

CLI Commands

Generate Speech

# Basic generation (default voice)
pocket-tts generate --text "Hello world"

# Custom voice (local file, URL, or safetensors)
pocket-tts generate --voice ./my_voice.wav
pocket-tts generate --voice "hf://kyutai/tts-voices/alba-mackenna/casual.wav"
pocket-tts generate --voice ./voice.safetensors

# Quality tuning
pocket-tts generate --temperature 0.7 --lsd-decode-steps 3

See docs/generate.md for full CLI reference.

Start Web Server

# Start FastAPI server with web UI
pocket-tts serve

# Custom host/port
pocket-tts serve --host localhost --port 8080

See docs/serve.md for server options.

Export Voice Embeddings

Convert audio files to .safetensors for faster loading:

# Single file
pocket-tts export-voice voice.mp3 voice.safetensors

# Batch conversion
pocket-tts export-voice voices/ embeddings/ --truncate

See docs/export_voice.md for export options.

Python API

Basic Usage

from pocket_tts import TTSModel
import scipy.io.wavfile

# Load model
model = TTSModel.load_model()

# Get voice state
voice = model.get_state_for_audio_prompt(
    "hf://kyutai/tts-voices/alba-mackenna/casual.wav"
)

# Generate audio
audio = model.generate_audio(voice, "Hello world!")

# Save
scipy.io.wavfile.write("output.wav", model.sample_rate, audio.numpy())

Load Model

model = TTSModel.load_model(
    config="b6369a24",       # Model variant
    temp=0.7,                # Temperature (0.5-1.0)
    lsd_decode_steps=1,      # Generation steps (1-5)
    eos_threshold=-4.0       # End-of-sequence threshold
)

Voice State

# From audio file/URL
voice = model.get_state_for_audio_prompt("./voice.wav")
voice = model.get_state_for_audio_prompt("hf://kyutai/tts-voices/alba-mackenna/casual.wav")

# From safetensors (fast loading)
voice = model.get_state_for_audio_prompt("./voice.safetensors")

Streaming Generation

# Stream audio chunks
for chunk in model.generate_audio_stream(voice, "Long text..."):
    # Process/save/play each chunk as generated
    print(f"Chunk: {chunk.shape[0]} samples")

Multi-Voice Management

# Preload multiple voices
voices = {
    "casual": model.get_state_for_audio_prompt("hf://kyutai/tts-voices/alba-mackenna/casual.wav"),
    "announcer": model.get_state_for_audio_prompt("./announcer.safetensors"),
}

# Use different voices
audio1 = model.generate_audio(voices["casual"], "Hey there!")
audio2 = model.generate_audio(voices["announcer"], "Breaking news!")

See docs/python-api.md for complete API reference.

Available Voices

Pre-made voices from hf://kyutai/tts-voices/:

alba-mackenna/casual.wav (default, female)
jessica-jian/casual.wav (female)
voice-donations/Selfie.wav (male, marius)
voice-donations/Butter.wav (male, javert)
ears/p010/freeform_speech_01.wav (male, jean)
vctk/p244_023.wav (female, fantine)
vctk/p262_023.wav (female, eponine)
vctk/p303_023.wav (female, azelma)

Or clone any voice from your own audio samples.

Voice Cloning Tips

Clean audio - Remove background noise (use Adobe Podcast Enhance)
Length - 3-10 seconds of speech is ideal
Quality - Input quality affects output quality
Format - WAV, MP3, or any common audio format supported

Performance Tips

CPU-only - GPU provides no speedup (model too small, batch size 1)
2 cores - Uses only 2 CPU cores efficiently
Streaming - Low latency (<200ms to first chunk)
Safetensors - Pre-process voices to .safetensors for instant loading

Output Format

All commands output WAV files:

Sample rate: 24 kHz
Channels: Mono
Bit depth: 16-bit PCM

Pocket-TTS

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