Archives for 2001

Today I read a paper titled “Best-first Model Merging for Hidden Markov Model Induction”

The abstract is:
This report describes a new technique for inducing the structure of Hidden Markov Models from data which is based on the general `model merging’ strategy (Omohundro 1992).

The process begins with a maximum likelihood HMM that directly encodes the training data.

Successively more general models are produced by merging HMM states.

A Bayesian posterior probability criterion is used to determine which states to merge and when to stop generalizing.

The procedure may be considered a heuristic search for the HMM structure with the highest posterior probability.

We discuss a variety of possible priors for HMMs, as well as a number of approximations which improve the computational efficiency of the algorithm.

We studied three applications to evaluate the procedure.

The first compares the merging algorithm with the standard Baum-Welch approach in inducing simple finite-state languages from small, positive-only training samples.

We found that the merging procedure is more robust and accurate, particularly with a small amount of training data.

The second application uses labelled speech data from the TIMIT database to build compact, multiple-pronunciation word models that can be used in speech recognition.

Finally, we describe how the algorithm was incorporated in an operational speech understanding system, where it is combined with neural network acoustic likelihood estimators to improve performance over single-pronunciation word models..

Today I read a paper titled “Collaboration on reference to objects that are not mutually known”

The abstract is:
In conversation, a person sometimes has to refer to an object that is not previously known to the other participant.

We present a plan-based model of how agents collaborate on reference of this sort.

In making a reference, an agent uses the most salient attributes of the referent.

In understanding a reference, an agent determines his confidence in its adequacy as a means of identifying the referent.

To collaborate, the agents use judgment, suggestion, and elaboration moves to refashion an inadequate referring expression..

Today I read a paper titled “Extracting Noun Phrases from Large-Scale Texts: A Hybrid Approach and Its Automatic Evaluation”

The abstract is:
To acquire noun phrases from running texts is useful for many applications, such as word grouping,terminology indexing, etc.

The reported literatures adopt pure probabilistic approach, or pure rule-based noun phrases grammar to tackle this problem.

In this paper, we apply a probabilistic chunker to deciding the implicit boundaries of constituents and utilize the linguistic knowledge to extract the noun phrases by a finite state mechanism.

The test texts are SUSANNE Corpus and the results are evaluated by comparing the parse field of SUSANNE Corpus automatically.

The results of this preliminary experiment are encouraging..

Today I read a paper titled “Identifying Discourse Markers in Spoken Dialog”

The abstract is:
In this paper, we present a method for identifying discourse marker usage in spontaneous speech based on machine learning.

Discourse markers are denoted by special POS tags, and thus the process of POS tagging can be used to identify discourse markers.

By incorporating POS tagging into language modeling, discourse markers can be identified during speech recognition, in which the timeliness of the information can be used to help predict the following words.

We contrast this approach with an alternative machine learning approach proposed by Litman (1996).

This paper also argues that discourse markers can be used to help the hearer predict the role that the upcoming utterance plays in the dialog.

Thus discourse markers should provide valuable evidence for automatic dialog act prediction..

Today I read a paper titled “Distorted English Alphabet Identification : An application of Difference Boosting Algorithm”

The abstract is:
The difference-boosting algorithm is used on letters dataset from the UCI repository to classify distorted raster images of English alphabets.

In contrast to rather complex networks, the difference-boosting is found to produce comparable or better classification efficiency on this complex problem.

Today I read a paper titled “Knowledge and common knowledge in a distributed environment”

The abstract is:
Reasoning about knowledge seems to play a fundamental role in distributed systems.

Indeed, such reasoning is a central part of the informal intuitive arguments used in the design of distributed protocols.

Communication in a distributed system can be viewed as the act of transforming the system’s state of knowledge.

This paper presents a general framework for formalizing and reasoning about knowledge in distributed systems.

We argue that states of knowledge of groups of processors are useful concepts for the design and analysis of distributed protocols.

In particular, distributed knowledge corresponds to knowledge that is “distributed” among the members of the group, while common knowledge corresponds to a fact being “publicly known”.

The relationship between common knowledge and a variety of desirable actions in a distributed system is illustrated.

Furthermore, it is shown that, formally speaking, in practical systems common knowledge cannot be attained.

A number of weaker variants of common knowledge that are attainable in many cases of interest are introduced and investigated.

Today I read a paper titled “A Market-Oriented Programming Environment and its Application to Distributed Multicommodity Flow Problems”

The abstract is:
Market price systems constitute a well-understood class of mechanisms that under certain conditions provide effective decentralization of decision making with minimal communication overhead.

In a market-oriented programming approach to distributed problem solving, we derive the activities and resource allocations for a set of computational agents by computing the competitive equilibrium of an artificial economy.

WALRAS provides basic constructs for defining computational market structures, and protocols for deriving their corresponding price equilibria.

In a particular realization of this approach for a form of multicommodity flow problem, we see that careful construction of the decision process according to economic principles can lead to efficient distributed resource allocation, and that the behavior of the system can be meaningfully analyzed in economic terms..

Today I read a paper titled “General Theory of Image Normalization”

The abstract is:
We give a systematic, abstract formulation of the image normalization method as applied to a general group of image transformations, and then illustrate the abstract analysis by applying it to the hierarchy of viewing transformations of a planar object.