Module ctc 

Connectionist Temporal Classification (CTC).

CTC (Graves et al. 2006) enables training and decoding of sequence models whose output length differs from, and is not pre-aligned with, the target label sequence. This module provides:

• ctc_loss — the forward-backward CTC negative-log-likelihood loss over a blank-augmented label lattice, computed in log-space.
• ctc_log_occupancy — per-symbol posterior responsibilities (the basis of the CTC gradient).
• ctc_greedy_decode — best-path (arg-max) decoding with CTC collapse.
• ctc_prefix_beam_search — prefix-beam-search decoding that sums alignment multiplicities (Hannun et al. 2014).

Re-exports

pub use ctc_decode::CtcHypothesis;

pub use ctc_decode::ctc_greedy_decode;

pub use ctc_decode::ctc_prefix_beam_search;

pub use ctc_loss::ctc_log_occupancy;

pub use ctc_loss::ctc_loss;

pub use ctc_loss::ctc_loss_batch;

Modules

ctc_decode

CTC decoding: best-path (greedy) and prefix-beam search (Graves 2006; Hannun 2014).

ctc_loss

Connectionist Temporal Classification (CTC) loss (Graves et al. 2006).