Scaling Forced Alignment to End-User Devices

The paper presents two optimizations for forced alignment of audio to text using the Viterbi algorithm. The first optimization applies the Hirschberg algorithm to reduce memory usage from 140 GB to 5 MB for three‑hour inputs and speeds up alignment to one‑third the time of torchaudio on a CPU. The second optimization models alignment as a constrained random walk, enabling pruning that yields an additional 2× speedup on inputs longer than 20 minutes while maintaining over 98 % alignment accuracy.

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