[Paper Review] Anytime Algorithms for Speech Parsing?

Guenther Goerz, Marcus Kesseler|ArXiv.org|Jun 21, 1994

Natural Language Processing Techniques4 citations

TL;DR

This paper investigates the application of anytime algorithms to speech parsing using feature unification, proposing a limited form of anytime behavior in parsing by ensuring incomplete transactions are completed before interruption. The authors demonstrate that while traditional parsing is inherently contract-based rather than truly interruptible, their prototype achieves practical anytime-like performance through transaction completion guarantees, offering incremental results under time constraints.

ABSTRACT

This paper discusses to which extent the concept of ``anytime algorithms'' can be applied to parsing algorithms with feature unification. We first try to give a more precise definition of what an anytime algorithm is. We arque that parsing algorithms have to be classified as contract algorithms as opposed to (truly) interruptible algorithms. With the restriction that the transaction being active at the time an interrupt is issued has to be completed before the interrupt can be executed, it is possible to provide a parser with limited anytime behavior, which is in fact being realized in our research prototype.

Motivation & Objective

• To examine whether the anytime algorithm paradigm can be meaningfully applied to speech parsing with feature unification.
• To clarify the distinction between contract algorithms and truly interruptible anytime algorithms in the context of parsing.
• To design and implement a parsing system that provides limited anytime behavior by ensuring transaction integrity during interruptions.
• To evaluate the feasibility and performance of incremental parsing under time constraints in a real-time processing context.
• To demonstrate that transaction completion before interruption enables practical anytime-like behavior in parsing systems.

Proposed method

• The authors define an anytime algorithm as one that can return a valid result at any point during execution, with quality improving over time.
• They argue that standard parsing algorithms are contract algorithms—requiring full execution to produce a result—rather than truly interruptible anytime algorithms.
• A limited form of anytime behavior is achieved by enforcing that any active parsing transaction must complete before an interrupt is processed.
• The approach is implemented in a research prototype that supports incremental parsing with feature unification under time constraints.
• The system ensures that partial results are valid and usable, even if computation is interrupted, by deferring interruption until the current transaction finishes.
• The design leverages existing feature-automaton parsing techniques with added control logic to manage interrupt timing and transaction boundaries.

Experimental results

Research questions

• RQ1 Can the anytime algorithm paradigm be meaningfully applied to speech parsing with feature unification?
• RQ2 What distinguishes contract-based parsing from truly interruptible anytime algorithms in this context?
• RQ3 Is it possible to design a parsing system that provides incremental results under time constraints while maintaining result validity?
• RQ4 How can transaction integrity be preserved during interruptions to support practical anytime behavior?
• RQ5 What performance trade-offs arise when enforcing transaction completion before interruption in a parsing system?

Key findings

• The paper concludes that standard parsing algorithms are fundamentally contract-based rather than truly interruptible, limiting their classification as anytime algorithms.
• A practical form of anytime behavior can be achieved by requiring active transactions to complete before interruptions are processed.
• The proposed approach enables incremental, usable results even when execution is interrupted, satisfying key properties of anytime systems.
• The research prototype successfully demonstrates limited anytime behavior in speech parsing with feature unification.
• The method ensures result correctness and consistency by deferring interruptions until transaction completion, enhancing reliability in real-time environments.
• The work establishes a framework for integrating anytime behavior into parsing systems through transaction-level control, offering a viable alternative to full reprocessing.