Fully Differentiable Neural Forced Alignment via Soft Dynamic Programming
Forced alignment, a foundational task in speech recognition pipelines, has stalled at HMM-GMM baselines despite ASR's recent leap toward human parity. This work bridges that gap by proposing a fully differentiable neural architecture that replaces traditional generative models with an encoder-decoder design, splitting the alignment problem into phoneme identity and boundary detection branches. The shift matters because end-to-end differentiability unlocks joint optimization with modern ASR systems and downstream NLP tasks, potentially unblocking a long-neglected bottleneck in production speech workflows.
Modelwire context
ExplainerThe paper doesn't just propose a neural replacement for forced alignment; it specifically enables end-to-end joint optimization with ASR and downstream NLP tasks. That joint differentiability is the actual constraint being lifted, not merely accuracy on alignment itself.
This connects directly to the SFL-MTSC work from the same day, which tackled robustness and consistency failures in LLM-based spoken language understanding. Both papers address reliability gaps in speech-to-text pipelines, but from different angles: SFL-MTSC fixes inconsistent multi-intent parsing after ASR, while this work removes a bottleneck before it. Together they signal that production voice systems are being debugged from both ends. The forced alignment fix also echoes the constraint tax paper's theme: removing hidden incompatibilities between components (here, between alignment and modern ASR training) that benchmarks don't expose.
If a major ASR system (Whisper, Conformer-based, or similar) ships an update within the next 12 months that cites joint optimization with differentiable alignment as enabling a measurable WER improvement on low-resource languages, that confirms the architectural change matters in practice. Otherwise, it remains a theoretical fix to a problem production teams may have already worked around.
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MentionsForced Alignment · HMM-GMM · ASR · Phoneme Alignment
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