k2py 0.2.4

Python bindings for k2

k2py

Python bindings for k2

Features

• Efficient Streaming Decoding: OnlineDenseIntersecter for real-time forced alignment
• Cross-Platform: Supports Linux, macOS, and Windows
• Python 3.10+: Compatible with modern Python versions
• Built with pybind11: Fast C++ bindings with minimal overhead

Installation

From PyPI

pip install k2py

Usage

Basic Example

from k2py import OnlineDenseIntersecter, CreateFsaVecFromStr
import numpy as np

# Create FSA from string representation
fsa_str = "0 1 1 1.0\n1 2 2 1.0\n2"
result = CreateFsaVecFromStr(fsa_str, final_state=2)

# Initialize decoder
decoder = OnlineDenseIntersecter(
    result["fsa"],
    result["aux_labels"],
    search_beam=20.0,
    output_beam=8.0,
    min_active_states=30,
    max_active_states=10000
)

# Prepare acoustic scores (num_frames x vocab_size)
scores = np.random.randn(100, 50).astype(np.float32)

# Decode
lattice = decoder.DecodeWithArray(scores, return_lattice=True)

# Get final alignment result
alignment = decoder.Finish()
print(f"Token IDs: {alignment['token_ids']}")
print(f"Timestamps: {alignment['timestamps']}")
print(f"Durations: {alignment['durations']}")