We give a general complexity classification scheme for monotone computation, including monotone space-bounded and Turing machine models not previously considered. We propose monotone complexity classes including mAC i , mNC i , mLOGCFL, mBWBP , mL, mNL, mP , mBPP and mNP . We define a simple notion of monotone reducibility and exhibit complete problems. This provides a framework for stating existing results and asking new questions. We show that mNL (monotone nondeterministic log-space) is not closed under complementation, in contrast to Immerman's and Szelepcs 'enyi's nonmonotone result [Imm88, Sze87] that NL = co-NL; this is a simple extension of the monotone circuit depth lower bound of Karchmer and Wigderson [KW90] for st-connectivity. We also consider mBWBP (monotone bounded width branching programs) and study the question of whether mBWBP is properly contained in mNC 1 , motivated by Barrington's result [Bar89] that BWBP = NC 1 . Although we cannot answer t...

A text-based and spoken language processing framework based on the Constraint Dependency Grammar (CDG) developed by Maruyama [24, 25] is discussed. The scope of CDG is expanded to allow for the analysis of sentences containing lexically ambiguous words, to allow feature analysis in constraints, and to efficiently process multiple sentence candidates that are likely to arise in spoken language processing. The benefits of the CDG parsing approach are summarized. Additionally, the development of CDG grammars using our grammar tools and parser is discussed.

We analyze the owner concept for PRAMs. In OROW-PRAMs each memory cell has one distinct processor that is the only one allowed to write into this memory cell and one distinct processor that is the only one allowed to read from it. By symmetric pointer doubling, a new proof technique for OROW-PRAMs, it is shown that list ranking can be done in O(log n) time by an OROWPRAM and that LOGSPACE ` OROW-TIME(log n). Then we prove that OROW-PRAMs are a fairly robust model and recognize the same class of languages when the model is modified in several ways and that all kinds of PRAMs intertwine with the NC -hierarchy without timeloss. Finally it is shown that EREWPRAMs can be simulated by OREW-PRAMs and ERCW-PRAMs by ORCW-PRAMs. 3 This research was partially supported by the Deutsche Forschungsgemeinschaft, SFB 342, Teilprojekt A4 "Klassifikation und Parallelisierung durch Reduktionsanalyse" y E-mail: rossmani@lan.informatik.tu-muenchen.dbp.de Introduction Fortune and Wyllie introduced in...

Well investigated are growing context-sensitive languages (GCSL), i. e. languages defined by grammars that have only growing rules, where the left side of a growing rule is shorter than its right side. GCSL is characterized by quasi growing context-sensitive grammars (QGCSG), i. e. the rules therein are growing only with respect to a valuation of all the strings by a homomorphism to natural numbers with addition. In this paper we introduce weak growing context-sensitive grammars (WGCSG), i. e. grammars that are growing with a weighted valuation of all strings, where the weights are the values of a position valuation. Here we evaluate a string by summing up every product of a symbol value with its position value. For every position valuation which does not agree with the beginning of any exponential function, the corresponding class of WGCSGs characterizes CSL, shown by a somehow tricky proof. Such a valuation function is called unsteady. On the other hand all WGCSG related to steady ...

In this paper, we describe a system which is capable of utilizing a variety of knowledge sources to select the most appropriate parse for a spoken sentence. These knowledge sources include syntax, semantics, and contextual information. We discuss one way to utilize contextual information when determining the parse for a sentence. At its simplest level, the system can be thought of as a generalpurpose query answering system for multiple topical databases. The user's input would be processed by the language processor which interfaces to the databases with the goal of interacting with the correct database in order to provide a reasonable answer to the user's spoken request. Initially, it analyzes a word graph of sentence hypotheses provided by a speech recognizer using general syntactic and semantic rules. Then, if the utterance is still ambiguous, it utilizes contextspecific constraints to further refine the analysis. This brings us closer to developing a more general purpose interface f...

We extend the lower bound techniques of [14], to the unbounded-error probabilistic model. A key step in the argument is a generalization of Nepomnjasci's theorem from the Boolean setting to the arithmetic setting. This generalization is made possible, due to the recent discovery of logspace-uniform TC 0 circuits for iterated multiplication [9]. Here is an

This paper describes the parallelization of Constraint Dependency Grammar (CDG) parsing. Though CDG provides a flexible framework for text-based and spoken language parsing and has an expressivity strictly greater than context-free grammars (CFGs), it also has a relatively slow serial running time (i.e., O(n 4 )). However, a parallelization for this algorithm is derived which uses O(n 4 ) processors to parse in O(k) time for a CRCW P-RAM, where n is the number of words in the sentence and k, the number of constraints, is a grammatical constant. Additionally, the paper describes an implementation of the algorithm on the MasPar MP-1, which uses the special features of the machine (particularly the global router) and O(n 4 ) processors to obtain an O(k + log(n)) running time. Because the average length of an English sentence is on the order of 10 words, the MasPar MP-1 has sufficient processors (i.e., 16,000) for parsing a typical sentence. Previous work in parallel parsing has fo...

The question of how to integrate language models with speech recognition systems is becoming more important as speech recognition technology matures. For the purposes of this paper, we have classified the level of integration of current and past approaches into three categories: tightly-coupled, loosely-coupled, or semicoupled systems. We then argue that loose coupling is more appropriate given the current state of the art and given that it allows one to measure more precisely which components of the language model are most important. We will detail how the speech component in our approach interacts with the language model and discuss why we chose our language model. 1 Introduction State of the art speech recognition systems achieve high recognition accuracies only on tasks that have low perplexities. The perplexity of a task is, roughly speaking, the average number of choices at any decision point. The perplexity of a task is at a minimum when the true language model is known and co...

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Ever since the fundamental work of Cook from 1971, satisfiability has been recognized as a central problem in computational complexity. It is widely believed to be intractable, and yet till recently even a linear-time, logarithmic-space algorithm for satisfiability was not ruled out. In 1997 Fortnow, building on earlier work by Kannan, ruled out such an algorithm. Since then there has been a significant amount of progress giving non-trivial lower bounds on the computational complexity of satisfiability. In this article we survey the known lower bounds for the time and space complexity of satisfiability and closely related problems on deterministic, randomized, and quantum models with random access. We discuss the state-of-the-art results and present the underlying arguments in a unified framework. 1