2540895
Large margin hidden Markov models for speech recognition
In this paper, motivated by large margin classifiers in machine learning, we propose a novel method to estimate continuous-density hidden Markov model (CDHMM) for speech recognition according to the principle of maximizing the minimum multiclass separation margin. The approach is named large margin HMM. First, we show this type of large margin HMM estimation problem can be formulated as a constrained minimax optimization problem. Second, we propose to solve this constrained minimax optimization problem by using a penalized gradient descent algorithm, where the original objective function, i.e., minimum margin, is approximated by a differentiable function and the constraints are cast as penalty terms in the objective function. The new training method is evaluated in the speaker-independent isolated E-set recognition and the TIDIGITS connected digit string recognition tasks. Experimental results clearly show that the large margin HMMs consistently outperform the conventional HMM training methods. It has been consistently observed that the large margin training method yields significant recognition error rate reduction even on top of some popular discriminative training methods
18487363
Confidence measures for speech recognition: A survey
Abstract In speech recognition, confidence measures (CM) are used to evaluate reliability of recognition results. A good confidence measure can largely benefit speech recognition systems in many practical applications. In this survey, I summarize most research works related to confidence measures which have been done during the past 10–12 years. I will present all these approaches as three major categories, namely CM as a combination of predictor features, CM as a posterior probability, and CM as utterance verification. Then, I also introduce some recent advances in the area. Moreover, I will discuss capabilities and limitations of the current CM techniques and generally comment on today’s CM approaches. Based on the discussion, I will conclude the paper with some clues for future works.
206799544
A continuation method for (strongly) monotone variational inequalities
We consider the variational inequality problem, denoted by VIP(X, F), whereF is a strongly monotone function and the convex setX is described by some inequality (and possibly equality) constraints. This problem is solved by a continuation (or interior-point) method, which solves a sequence of certain perturbed variational inequality problems. These perturbed problems depend on a parameterμ > 0. It is shown that the perturbed problems have a unique solution for all values ofμ > 0, and that any sequence generated by the continuation method converges to the unique solution of VIP(X,F) under a well-known linear independence constraint qualification (LICQ). We also discuss the extension of the continuation method to monotone variational inequalities and present some numerical results obtained with a suitable implementation of this method. © 1998 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V.
20068677
A case study of parallel I/O for biological sequence search on Linux clusters
In this paper we analyze the I/O access patterns of a widely-used biological sequence search tool and implement two variations that employ parallel-I/O for data access based on PVFS (Parallel Virtual File System) and CEFT-PVFS (cost-effective fault-tolerant PVFS). Experiments show that the two variations outperform the original tool when equal or even fewer storage devices are used in the former. It is also found that although the performance of the two variations improves consistently when initially increasing the number of servers, this performance gain from parallel I/O becomes insignificant with further increase in server number. We examine the effectiveness of two read performance optimization techniques in CEFT-PVFS by using this tool as a benchmark. Performance results indicate: (1) doubling the degree of parallelism boosts the read performance to approach that of PVFS; and (2) skipping hot-spots can substantially improve the I/O performance when the load on data servers is highly imbalanced. The I/O resource contention due to the sharing of server nodes by multiple applications in a cluster has been shown to degrade the performance of the original tool and the variation based on PVFS by up to 10 and 21 folds, respectively; whereas, the variation based on CEFT-PVFS only suffered a two-fold performance degradation.
7586381
Dynamic Load Balancing for I/O-Intensive Tasks on Heterogeneous Clusters
Since I/O-intensive tasks running on a heterogeneous cluster need a highly effective usage of global I/O resources, previous CPU- or memory-centric load balancing schemes suffer significant performance drop under I/O-intensive workload due to the imbalance of I/O load. To solve this problem, we develop two I/O-aware load-balancing schemes, which consider system heterogeneity and migrate more I/O-intensive tasks from a node with high I/O utilization to those with low I/O utilization. If the workload is memory-intensive in nature, the new method applies a memory-based load balancing policy to assign the tasks. Likewise, when the workload becomes CPU-intensive, our scheme leverages a CPU-based policy as an efficient means to balance the system load. In doing so, the proposed approach maintains the same level of performance as the existing schemes when I/O load is low or well balanced. Results from a trace-driven simulation study show that, when a workload is I/O-intensive, the proposed schemes improve the performance with respect to mean slowdown over the existing schemes by up to a factor of 8. In addition, the slowdowns of almost all the policies increase consistently with the system heterogeneity.
34925945
Performance and configuration of hierarchical ring networks for multiprocessors
Analytical queueing network models for expected message delay in 2-level and 3-level hierarchical-ring interconnection networks (INs) are developed. Such networks have recently been used in commercial and research prototype multiprocessors. A major class of traffic carried by these INs consists of cache line transfers, and associated coherency control messages, between processor caches and remote memory modules in shared-memory multiprocessors. Memory modules are assumed to be evenly distributed over the processor nodes. Such traffic consists of short, fixed-length messages. They can be conveniently transported using the slotted ring transmission technique, which is studied here. The message delay results derived from the models are shown to be quite accurate when checked against a simulation study. The comparisons to simulations include heavy traffic situations where queueing delays in ring crossover switches are significant for ring utilization levels of 80 to 90%. As well as facilitating analysis, the analytical models can be used to determine optimal sizes for the rings at different levels in the hierarchy under specified traffic distributions in a system with a given total number of processor nodes. Optimality is in terms of minimizing average message delay. A specific example of such a design exercise is provided for the uniform traffic case.
17152151
Application of fuzzy measures in multi-criteria evaluation in GIS
Multi-criteria evaluation (MCE) is perhaps the most fundamental of decision support operations in geographical information systems (GIS). This paper reviews two main MCE approaches employed in GIS, namely Boolean and Weighted Linear Combination (WLC), and discusses issues and problems associated with both. To resolve the conceptual differences between the two approaches, this paper proposes the application of fuzzy measures, a concept that is broader but that includes fuzzy set membership, and argues that the standardized factors of MCE belong to a general class of fuzzy measures and the more specific instance of fuzzy set membership. This perspective provides a strong theoretical basis for the standardization of factors and their subsequent aggregation. In this context, a new aggregation operator that accommodates and extends the Boolean and WLC approaches is discussed: the Ordered Weighted Average. A case study of industrial allocation in Nakuru, Kenya is employed to illustrate the different approaches.