The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Alon Lavie - One of the best experts on this subject based on the ideXlab platform.
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ECAI Workshop on Dialogue Processing in Spoken Language Systems - Minimizing Cumulative Error in Discourse Context
Dialogue Processing in Spoken Language Systems, 1997Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
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ICSLP - Dialogue processing in a conversational speech translation system
Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, 1996Co-Authors: Alon Lavie, M. Gavalada, Laura Mayfield, Lori Levin, Donna Gates, Y. Qu, Alex Waibel, Maite TaboadaAbstract:Attempts at discourse processing of spontaneously spoken dialogue face several difficulties: multiple hypotheses that result from the parser's attempts to make sense of the output from the speech recognizer, ambiguity that results from segmentation of multi-sentence utterances, and Cumulative Error-Errors in the discourse context which cause further Errors when subsequent sentences are processed. In this paper we describe how the JANUS multi-lingual speech-to-speech translation system addresses problems that arise in discourse processing of spontaneous speech. We describe our robust parsers, our procedures for segmenting long utterances, and two approaches to discourse processing that attempt to deal with ambiguity and Cumulative Error.
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minimizing Cumulative Error in discourse context
European Conference on Artificial Intelligence, 1996Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
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Dialogue processing in a conversational speech translation system
Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, 1996Co-Authors: Alon Lavie, M. Gavalada, Laura Mayfield, Lori Levin, Donna Gates, Y. Qu, Alex Waibel, Maite TaboadaAbstract:Attempts at discourse processing of spontaneously spoken dialogue\nface several difficulties: multiple hypotheses that result from the\nparser's attempts to make sense of the output from the speech\nrecognizer, ambiguity that results from segmentation of multi-sentence\nutterances, and Cumulative Error-Errors in the discourse context which\ncause further Errors when subsequent sentences are processed. In this\npaper we describe how the JANUS multi-lingual speech-to-speech\ntranslation system addresses problems that arise in discourse processing\nof spontaneous speech. We describe our robust parsers, our procedures\nfor segmenting long utterances, and two approaches to discourse\nprocessing that attempt to deal with ambiguity and Cumulative\nError
Lori Levin - One of the best experts on this subject based on the ideXlab platform.
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ECAI Workshop on Dialogue Processing in Spoken Language Systems - Minimizing Cumulative Error in Discourse Context
Dialogue Processing in Spoken Language Systems, 1997Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
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ICSLP - Dialogue processing in a conversational speech translation system
Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, 1996Co-Authors: Alon Lavie, M. Gavalada, Laura Mayfield, Lori Levin, Donna Gates, Y. Qu, Alex Waibel, Maite TaboadaAbstract:Attempts at discourse processing of spontaneously spoken dialogue face several difficulties: multiple hypotheses that result from the parser's attempts to make sense of the output from the speech recognizer, ambiguity that results from segmentation of multi-sentence utterances, and Cumulative Error-Errors in the discourse context which cause further Errors when subsequent sentences are processed. In this paper we describe how the JANUS multi-lingual speech-to-speech translation system addresses problems that arise in discourse processing of spontaneous speech. We describe our robust parsers, our procedures for segmenting long utterances, and two approaches to discourse processing that attempt to deal with ambiguity and Cumulative Error.
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minimizing Cumulative Error in discourse context
European Conference on Artificial Intelligence, 1996Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
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Dialogue processing in a conversational speech translation system
Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96, 1996Co-Authors: Alon Lavie, M. Gavalada, Laura Mayfield, Lori Levin, Donna Gates, Y. Qu, Alex Waibel, Maite TaboadaAbstract:Attempts at discourse processing of spontaneously spoken dialogue\nface several difficulties: multiple hypotheses that result from the\nparser's attempts to make sense of the output from the speech\nrecognizer, ambiguity that results from segmentation of multi-sentence\nutterances, and Cumulative Error-Errors in the discourse context which\ncause further Errors when subsequent sentences are processed. In this\npaper we describe how the JANUS multi-lingual speech-to-speech\ntranslation system addresses problems that arise in discourse processing\nof spontaneous speech. We describe our robust parsers, our procedures\nfor segmenting long utterances, and two approaches to discourse\nprocessing that attempt to deal with ambiguity and Cumulative\nError
Carolyn Penstein Rose - One of the best experts on this subject based on the ideXlab platform.
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ECAI Workshop on Dialogue Processing in Spoken Language Systems - Minimizing Cumulative Error in Discourse Context
Dialogue Processing in Spoken Language Systems, 1997Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
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minimizing Cumulative Error in discourse context
European Conference on Artificial Intelligence, 1996Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
A. Kumar - One of the best experts on this subject based on the ideXlab platform.
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Optimal configuration of OSPF aggregates
IEEE ACM Transactions on Networking, 2003Co-Authors: R. Rastogi, Y. Breitbart, M. Garofalakis, A. KumarAbstract:Open Shortest Path First (OSPF) is a popular protocol for routing within an autonomous system (AS) domain. In order to scale for large networks containing hundreds and thousands of subnets, OSPF supports a two-level hierarchical routing scheme through the use of OSPF areas. Subnet addresses within an area are aggregated, and this aggregation is a crucial requirement for scaling OSPF to large AS domains, as it results in significant reductions in routing table sizes, smaller link-state databases, and less network traffic to synchronize the router link-state databases. On the other hand, address aggregation also implies loss of information about the length of the shortest path to each subnet, which in turn, can lead to suboptimal routing.In this paper, we address the important practical problem of configuring OSPF aggregates to minimize the Error in OSPF shortest-path computations due to subnet aggregation. We first develop an optimal dynamic programming algorithm that, given an upper bound k on the number of aggregates to be advertised and a weight assignment function for the aggregates, computes the k aggregates that result in the minimum Cumulative Error in the shortest-path computations for all source-destination subnet pairs. Subsequently, we tackle the problem of assigning weights to OSPF aggregates such that the Cumulative Error in the computed shortest paths is minimized. We demonstrate that, while for certain special cases (e.g., unweighted Cumulative Error) efficient optimal algorithms for the weight assignment problem can be devised, the general problem itself is NP-hard. Consequently, we have to rely on search heuristics to solve the weight assignment problem. To the best of our knowledge, our work is the first to address the algorithmic issues underlying the configuration of OSPF aggregates and to propose efficient configuration algorithms that are provably optimal for many practical scenarios.
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Optimal configuration of OSPF aggregates
IEEE ACM Transactions on Networking, 2003Co-Authors: R. Rastogi, Y. Breitbart, M. Garofalakis, A. KumarAbstract:Open Shortest Path First (OSPF) is a popular protocol for routing within an autonomous system (AS) domain. In order to scale for large networks containing hundreds and thousands of subnets, OSPF supports a two-level hierarchical routing scheme through the use of OSPF areas. Subnet addresses within an area are aggregated, and this aggregation is a crucial requirement for scaling OSPF to large AS domains, as it results in significant reductions in routing table sizes, smaller link-state databases, and less network traffic to synchronize the router link-state databases. On the other hand, address aggregation also implies loss of information about the length of the shortest path to each subnet, which in turn, can lead to suboptimal routing. We address the important practical problem of configuring OSPF aggregates to minimize the Error in OSPF shortest-path computations due to subnet aggregation. We first develop an optimal dynamic programming algorithm that, given an upper bound k on the number of aggregates to be advertised and a weight assignment function for the aggregates, computes the k aggregates that result in the minimum Cumulative Error in the shortest-path computations for all source-destination subnet pairs. Subsequently, we tackle the problem of assigning weights to OSPF aggregates such that the Cumulative Error in the computed shortest paths is minimized. We demonstrate that, while for certain special cases (e.g., unweighted Cumulative Error) efficient optimal algorithms for the weight assignment problem can be devised, the general problem itself is NP-hard. Consequently, we have to rely on search heuristics to solve the weight assignment problem. To the best of our knowledge, our work is the first to address the algorithmic issues underlying the configuration of OSPF aggregates and to propose efficient configuration algorithms that are provably optimal for many practical scenarios.
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INFOCOM - Optimal configuration of OSPF aggregates
Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, 2002Co-Authors: R. Rastogi, Y. Breitbart, M. Garofalakis, A. KumarAbstract:Open shortest path first (OSPF) is a popular protocol for routing within an autonomous system (AS) domain. In this paper, we address the important practical problem of configuring OSPF aggregates to minimize the Error in OSPF shortest path computations due to subnet aggregation. We first develop an optimal dynamic programming algorithm that, given an upper bound k on the number of aggregates to be advertised and a weight-assignment function for the aggregates, computes the k aggregates that result in the minimum Cumulative Error in the shortest path computations for all source-destination subnet pairs. Subsequently, we tackle the problem of assigning weights to OSPF aggregates such that the Cumulative Error in the computed shortest paths is minimized. We demonstrate that, while for certain special cases (e.g., unweighted Cumulative Error) efficient optimal algorithms for the weight-assignment problem can be devised, the general problem itself is /spl Nscr//spl Pscr/-hard. Consequently, we have to rely on search heuristics to solve the weight-assignment problem. To the best of our knowledge, our work is the first to address the algorithmic issues underlying the configuration of OSPF aggregates and to propose efficient configuration algorithms that are provably optimal for many practical scenarios.
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Optimal configuration of OSPF aggregates
Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies, 2002Co-Authors: R. Rastogi, Y. Breitbart, M. Garofalakis, A. KumarAbstract:Open shortest path first (OSPF) is a popular protocol for routing within an autonomous system (AS) domain. In this paper, we address the important practical problem of configuring OSPF aggregates to minimize the Error in OSPF shortest path computations due to subnet aggregation. We first develop an optimal dynamic programming algorithm that, given an upper bound k on the number of aggregates to be advertised and a weight-assignment function for the aggregates, computes the k aggregates that result in the minimum Cumulative Error in the shortest path computations for all source-destination subnet pairs. Subsequently, we tackle the problem of assigning weights to OSPF aggregates such that the Cumulative Error in the computed shortest paths is minimized. We demonstrate that, while for certain special cases (e.g., unweighted Cumulative Error) efficient optimal algorithms for the weight-assignment problem can be devised, the general problem itself is /spl Nscr//spl Pscr/-hard. Consequently, we have to rely on search heuristics to solve the weight-assignment problem. To the best of our knowledge, our work is the first to address the algorithmic issues underlying the configuration of OSPF aggregates and to propose efficient configuration algorithms that are provably optimal for many practical scenarios.
Yan Qu - One of the best experts on this subject based on the ideXlab platform.
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ECAI Workshop on Dialogue Processing in Spoken Language Systems - Minimizing Cumulative Error in Discourse Context
Dialogue Processing in Spoken Language Systems, 1997Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
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minimizing Cumulative Error in discourse context
European Conference on Artificial Intelligence, 1996Co-Authors: Yan Qu, Lori Levin, Alon Lavie, Barbara Di Eugenio, Carolyn Penstein RoseAbstract:Cumulative Error limits the usefulness of context in applications utilizing contextual information. It is especially a problem in spontaneous speech systems where unexpected input, out-of-domain utterances and missing information are hard to fit into the standard structure of the contextual model. In this paper we discuss how our approaches to recognizing speech acts address the problem of Cumulative Error. We demonstrate the advantage of the proposed approaches over those that do not address the problem of Cumulative Error. The experiments are conducted in the context of Enthusiast, a large Spanish-to-English speech-to-speech translation system in the appointment scheduling domain [10, 5, 11].
