GPU-Accelerated Viterbi Exact Lattice Decoder forBatched Online and Offline Speech Recognition
Table 3: Comparison of FST size and WER/Speed.
['[BOLD] LM', '[BOLD] HCLG  [BOLD] Size (MB)', '[BOLD] test-clean  [BOLD] xRTF', '[BOLD] test-clean  [BOLD] WER', '[BOLD] test-other  [BOLD] xRTF', '[BOLD] test-other  [BOLD] WER']
Three different trigram language models with different pruning thresholds (3e−10, 1e−10, and no pruning, respectively) are used with other parameters held constant. Despite a 10x filesize difference, the decode performs faster using the large language model likely due to reduced perplexity during decoding yielding extra pruning, and subsequently improved speed.