Daniel Jurafsky

Rion Snow, Daniel Jurafsky, Andrew Y. Ng

Abstract (2008)

discovery

Book Reviews Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2008)

Daniel Jurafsky, James H. Martin

Processing Conference (Benjamins) Verb Sense and Verb Subcategorization Probabilities (2008)

In ACL/COLING-98 Workshop on Discourse Relations and Discourse Markers Lexical, Prosodic, and Syntactic Cues for Dialog Acts (2008)

The probabilistic relation between verbs and their arguments plays an important role in psychological theories of human language processing. For example, Ford, Bresnan and Kaplan (1982) proposed that...

Daniel Jurafsky, Elizabeth Shriberg, Barbara Fox, Traci Curl

The structure of a discourse is reflected in many aspects of its linguistic realization, including its lexical, prosodic, syntactic, and semantic nature. Multiparty dialog contains a particular kind...

Verb Subcategorization Frequency Differences between Business- News and Balanced Corpora: The Role of Verb Sense (2008)

Douglas Rol, Daniel Jurafsky, Lise Menn, Susanne Gahl, Elizabeth Elder

{douglas.roland, jurafsky, lise.menn,

To appear in ICSLP-94 (2008)

Daniel Jurafsky, Chuck Wooters, Gary Tajchman, Jonathan Segal, Andreas Stolcke, Eric Fosler, ...

This paper describes the architecture and performance of the Berkeley Restaurant Project (BeRP), a medium-vocabulary, speaker-independent, spontaneous continuous speech understanding system currently...

Processing Conference (Benjamins) Verb Sense and Verb Subcategorization Probabilities (2007)

In press, Cognitive Science A Probabilistic Model of Lexical and Syntactic Access and Disambiguation (2007)

The probabilistic relation between verbs and their arguments plays an important role in psychological theories of human language processing. For example, Ford, Bresnan and Kaplan (1982) proposed that...

To appear, Journal of the Acoustical Society of America Effects of disfluencies, predictability, and utterance position on word form variation in English conversation (2007)

The problems of access – retrieving linguistic structure from some mental grammar – and disambiguation – choosing among these structures to correctly parse ambiguous linguistic input – are...

Alan Bell, Daniel Jurafsky, Eric Fosler-lussier, Cynthia Girand, Gregory Gildea

Function words, especially frequently occurring ones such as (the, that, and, and of), vary widely in pronunciation. Understanding this variation is essential both for cognitive modeling of lexical...

In ACL/COLING-98 Workshop on Discourse Relations and Discourse Markers Lexical, Prosodic, and Syntactic Cues for Dialog Acts (2007)

Daniel Jurafsky, Elizabeth Shribergy, Traci Curl

The structure of a discourse is reflected in many aspects of its linguistic realization, including its lexical, prosodic, syntactic, and semantic nature. Multiparty dialog contains a particular kind...

In press, Language UNIVERSAL TENDENCIES IN THE SEMANTICS OF THE DIMINUTIVE (2007)

To appear in ICASSP-95 USING A STOCHASTIC CONTEXT-FREE GRAMMAR AS A LANGUAGE MODEL FOR SPEECH RECOGNITION (2007)

Despite the crucial dependence of synchronic meaning on both historical and cognitive context, we have traditionally used different tools for capturing synchronic and diachronic generalizations in...

Daniel Jurafsky, Chuck Wooters, Jonathan Segal, Andreas Stolcke, Gary Tajchman, Nelson Morgan

This paper describes a number of experiments in adding new grammatical knowledge to the Berkeley Restaurant Project (BeRP), our medium-vocabulary (1300 word), speaker-independent, spontaneous...

DRAFT: DO NOT CITE WITHOUT PERMISSION. Running head: COMMON GROUND IN PRODUCTION Common Ground in Production: Effects of Mutual Knowledge on Word Duration (2007)

Michelle L. Gregory, Alice F. Healy, Daniel Jurafsky

Common Ground in Production 2 A key issue in models of lexical production is whether a model of hearer knowledge influences speakers ’ productions. In this study we investigate whether the...

SRI International (2007)

Andreas Stolcke, Noah Coccaro, Rebecca Bates, Paul Taylor, Klaus Ries, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-

Submitted to ICASSP-95 USING A STOCHASTIC CONTEXT-FREE GRAMMAR AS A LANGUAGE MODEL FOR SPEECH RECOGNITION (2007)

Daniel Jurafsky, Chuck Wooters, Jonathan Segal, Andreas Stolcke, Eric Fosler, Gary Tajchman, ...

This paper describes a number of experiments in adding new grammatical knowledge to the Berkeley Restaurant Project (BeRP), our medium-vocabulary (1300 word), speaker-independent, spontaneous...

Submitted to Journal of the Acoustical Society of America. Comments (2007)

Alan Bell, Daniel Jurafsky, Eric Fosler-lussiery, Cynthia Girand, Michelle Gregory, Daniel Gildeay

appreciated, but do not quote without permission. Form variation of English function words in conversation

2001b. The effect of language model probability on pronunciation reduction (2007)

Daniel Jurafsky, Alan Bell, Michelle Gregory, William D. Raymond

We investigate how the probability of a word affects its pronunciation. We examined 5618 tokens of the 10 most frequent (function) words in Switchboard: I, and, the, that, a, you, to, of, it, and in,...

Have we met? MDP based speaker id for robot dialogue (2006)

Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky, Andrew Y. Ng

We present a novel approach to speaker identification in robot dialogue that allows a robot to recognize people during natural conversation and address them by name. Our STanford AI Robot (STAIR)...

Semantic role chunking combining complementary syntactic views (2005)

Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James H. Martin, Daniel Jurafsky

This paper describes a semantic role labeling system that uses features derived from different syntactic views, and combines them within a phrase-based chunking paradigm. For an input sentence,...

Support vector learning for semantic argument classification (2005)

Sameer Pradhan, Kadri Hacioglu, Valerie Krugler, Wayne Ward, James H. Martin, Daniel Jurafsky

Abstract. The natural language processing community has recently experienced a growth of interest in domain independent shallow semantic parsing – the process of assigning a WHO did WHAT to WHOM,...

The detection of emphatic words using acoustic and lexical features (2005)

Jason M. Brenier, Daniel M. Cer, Daniel Jurafsky

In this study, we describe an automatic detector for prosodically salient or emphasized words in speech. Knowledge of whether a word is emphatic or not could improve Text-to-Speech synthesis as well...

Proceedings of the 9th Conference on Computational Natural Language Learning (CoNLL), (2005)

Pages Ann Arbor, Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James H. Martin, Daniel Jurafsky

This paper describes a semantic role labeling system that uses features derived from different syntactic views, and combines them within a phrase-based chunking paradigm. For an input sentence,...

Support vector learning for semantic argument classification (2005)

Sameer Pradhan, Kadri Hacioglu, Valerie Krugler, Wayne Ward, James H. Martin, Daniel Jurafsky

Abstract. The natural language processing community has recently experienced a growth of interest in domain independent shallow semantic parsing – the process of assigning a WHO did WHAT to WHOM,...

EFFECTIVE STATISTICAL MODELS FOR SYNTACTIC AND SEMANTIC DISAMBIGUATION (2005)

Christopher D. Manning, Andrew Y. Ng, Daniel Jurafsky

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Semantic role chunking combining complementary syntactic views (2005)

Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James H. Martin, Daniel Jurafsky

This paper describes a semantic role labeling system that uses features derived from different syntactic views, and combines them within a phrase-based chunking paradigm. For an input sentence,...

Semantic role labeling by tagging syntactic chunks (2004)

Kadri Hacioglu, Sameer Pradhan, Wayne Ward, James H. Martin, Daniel Jurafsky

In this paper, we present a semantic role labeler (or chunker) that groups syntactic chunks (i.e. base phrases) into the arguments of a predicate. This is accomplished by casting the semantic...

Automatic tagging of Arabic text: from raw text to base phrase chunks (2004)

Mona Diab, Kadri Hacioglu, Daniel Jurafsky

To date, there are no fully automated systems addressing the community’s need for fundamental language processing tools for Arabic text. In this paper, we present a Support Vector Machine (SVM)...

Parsing Arguments of Nominalizations in English and Chinese (2004)

Sameer Pradhan, Honglin Sun, Wayne Ward, James H. Martin, Daniel Jurafsky

In this paper, we use a machine learning framework for semantic argument parsing, and apply it to the task of parsing arguments of eventive nominalizations in the FrameNet database. We create a...

Semantic Role Labeling by Tagging Syntactic Chunks (2004)

Kadri Hacioglu, Sameer Pradhan, Wayne Ward, James H. Martin, Daniel Jurafsky

In this paper, we present a semantic role labeler (or chunker) that groups syntactic chunks (i.e. base phrases) into the arguments of a predicate.

Semantic role parsing: Adding semantic structure to unstructured text (2003)

Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James H. Martin, Daniel Jurafsky

There is a ever-growing need to add structure in the form of semantic markup to the huge amounts of unstructured text data now available. We present the technique of shallow semantic parsing, the...

A Bayesian model predicts human parse preference and reading time in sentence processing (2002)

Automatic labeling of semantic roles (2002)

Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension process with Bayesian...

The role of the lemma in form variation (2002)

We present a system for identifying the semantic relationships, or semantic roles, lled by constituents of a sentence within a semantic frame. Given an input sentence and a target word and frame, the...

Daniel Jurafsky, Alan Bell, Cynthia Gir

A key problem in building a complete model of the lexicon is understanding the

Automatic labeling of semantic roles (2002)

Automatic labeling of semantic roles (2002)

We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Given an input sentence and a target word and frame,...

Which Predictability Measures Affect Content Word Durations? (2002)

We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Given an input sentence and a target word and frame,...

Alan Bell, Michelle L. Gregory, Jason M. Brenier, Daniel Jurafsky, Ayako Ikeno, Cynthia Girand

The pronunciation of a word can vary widely, and many factors are known to affect this variation. This paper focuses on the role of predictability on word duration. Previous research has suggested...

A Bayesian model predicts human parse preference and reading time in sentence processing (2002)

A Bayesian model predicts human parse preference and reading time in sentence processing (2002)

Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension process with Bayesian...

A Bayesian model predicts human parse preference and reading time in sentence processing (2002)

Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension process with Bayesian...

Language-independent induction of part of speech class labels using only language universals (2001)

Narayanan and Jurafsky (1998) proposed that human language comprehension can be modeled by treating human comprehenders as Bayesian reasoners, and modeling the comprehension process with Bayesian...

Knowledge-free induction of inflectional morphologies (2001)

We introduce a language-independent strategy for inducing part of speech tags from corpora. Unlike other techniques that use language-specific lexicons, rulesets, and so forth to tag, our algorithm...

Knowledge-free induction of inflectional morphologies (2001)

We propose an algorithm to automatically induce the morphology of inflectional languages using only text corpora and no human input. Our algorithm combines cues from orthography, semantics, and...

Probabilistic relations between words: Evidence from reduction in lexical production (2001)

We propose an algorithm to automatically induce the morphology of inflectional languages using only text corpora and no human input. Our algorithm combines cues from orthography, semantics, and...

Daniel Jurafsky, Alan Bell, Michelle Gregory, William D. Raymond

2000. Frequency and the emergence of linguistic

Probabilistic relations between words: Evidence from reduction in lexical production (2001)

Daniel Jurafsky, Alan Bell, Michelle Gregory, William D. Raymond

2000. Frequency and the emergence of linguistic

Knowledge-free induction of inflectional morphologies (2001)

The Effect of Language Model Probability on Pronunciation Reduction (2001)

We propose an algorithm to automatically induce the morphology of inflectional languages using only text corpora and no human input. Our algorithm combines cues from orthography, semantics, and...

Daniel Jurafsky, Alan Bell, Michelle Gregory, William D. Raymond

We investigate how the probability of a word affects its pronunciation. We examined 5618 tokens of the 10 most frequent (function) words in Switchboard: I, and, the, that, a, you, to, of, it, and in,...

Dialogue act modeling for automatic tagging and recognition of conversational speech (2000)

Stolcke, Andreas, Coccaro, Noah, Bates, Rebecca, Taylor, Paul, Ries, Klaus, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as STATEMENT, QUESTION, BACKCHANNEL, AGREEMENT, DISAGREEMENT, and APOLOGY. Our...

Dialogue act modeling for automatic tagging and recognition of conversational speech (2000)

Stolcke, Andreas, Coccaro, Noah, Bates, Rebecca, Taylor, Paul, Ries, Klaus, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as STATEMENT, QUESTION, BACKCHANNEL, AGREEMENT, DISAGREEMENT, and APOLOGY. Our...

Speech and Language Processing : An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2000)

Jurafsky, Daniel, Martin, James H., Norvig, Peter (pról.), Russell, Stuart Jonathan (pról.)

Obra en que se ofrece una revisión unificada del procesamiento de voz y lenguaje, a partir de la presentación de algoritmos y técnicas de procesamiento del lenguaje natural basadas tanto en voz...

Speech and Language Processing : An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition (2000)

Jurafsky, Daniel, Martin, James H., Norvig, Peter (pról.), Russell, Stuart Jonathan (pról.)

0-13-095069-6

Dialogue act modeling for automatic tagging and recognition of conversational speech (2000)

Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speechact-like

Dialogue act modeling for automatic tagging and recognition of conversational speech (2000)

Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speechact-like

Dialogue act modeling for automatic tagging and recognition of conversational speech (2000)

Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speechact

Knowledge-free induction of morphology using Latent Semantic Analysis (2000)

Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech (2000)

Morphology induction is a subproblem of important tasks like automatic learning of machine-readable dictionaries and grammar induction. Previous morphology induction approaches have relied solely on...

Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, ...

this article is twofold: On the one hand, we aim to present a comprehensive framework for modeling and automatic classification of DAs, founded on well-known statistical methods. In doing so, we will...

Verb Subcategorization Frequency Differences between BusinessNews and Balanced Corpora: The Role of Verb Sense (2000)

Douglas Roland, Daniel Jurafsky, Lise Menn, Susanne Gahl, Elizabeth Elder, Chris Riddoch

We explore the differences in verb subcategorization frequencies across several corpora in an effort to obtain stable cross corpus subcategorization probabilities for use in norming psychological...

The Role of the Lemma in Form Variation (2000)

Daniel Jurafsky, Alan Bell, Cynthia Girand

this paper we examine the role of the lemma in explaining these kinds of variation. For example, consider the word to. Here a single wordform /tu/ is shared by (at least) two lemmas: an infinitive...

Knowledge-Free Induction of Morphology Using Latent Semantic Analysis (2000)

Automatic Labeling of Semantic Roles (2000)

Morphology induction is a subproblem of important tasks like automatic learning of machine-readable dictionaries and grammar induction. Previous morphology induction approaches have relied solely on...

Probabilistic Relations between Words: Evidence from Reduction in Lexical Production (2000)

We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Various lexical and syntactic features are derived...

Daniel Jurafsky, Alan Bell, Michelle Gregory, William D. Raymond

this paper we focus on a particular domain of probabilistic linguistic knowledge in lexical production: the role of local probabilistic relations between words. 1

Verb Sense and Verb Subcategorization Probabilities (2000)

Verb Sense and Verb Subcategorization Probabilities (2000)

this paper we measure these probabilities only for syntactic argument frames, but the Lemma Argument Probability hypothesis bears equally on the semantic/thematic expectations shown by studies such...

Dialogue act modeling for automatic tagging and recognition of conversational speech (2000)

this paper we measure these probabilities only for syntactic argument frames, but the Lemma Argument Probability hypothesis bears equally on the semantic/thematic expectations shown by studies such...

Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, ...

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speechact-like

The Role of the Lemma in Form Variation (2000)

Carlos Gussenhoven, Daniel Jurafsky, Alan Bell, Cynthia Gir

A key problem in building a complete model of the lexicon is understanding the

Verb subcategorization frequency differences between business-news and balanced corpora: The role of verb sense (2000)

Daniel Jurafsky, Lise Menn, Susanne Gahl, Elizabeth Elder

{douglas.roland, jurafsky, lise.menn,

Forms of English function words – Effects of disfluencies, turn position, age and sex, and predictability (1999)

Alan Bell, Daniel Jurafsky, Cynthia Gir, Daniel Gildea

This study examines the role of several non–phonetic factors in the reduction of ten frequent English function words (I, and, the, that, a, you, to, of, it, and in) in the phoneticallytranscribed...

The Effects of Collocational Strength and Contextual Predictability in Lexical Production (1999)

Michelle L. Gregory, William D. Raymond, Alan Bell, Eric Fosler-lussier, Daniel Jurafsky

This paper extends this probabilistic hypothesis to language production, suggesting that speakers use their knowledge of the probability of a word or combinations of words in sentence production. In...

Disfluencies, (1999)

Position Predictability Alan, Alan Bell, Daniel Jurafsky, Cynthia Gir, Daniel Gildea

This study examines the role of several non--phonetic factors in the reduction of ten frequent English function words ( I, and, the, that, a , you, to, of, it, and in) in the phoneticallytranscribed...

Forms of English Function Words - Effects of Disfluencies, Turn Position, Age and Sex, and Predictability (1999)

Alan Bell, Daniel Jurafsky, Eric Fosler-Lussier, Cynthia Girand, Daniel Gildea

This study examines the role of several non--phonetic factors in the reduction of ten frequent English function words ( I, and, the, that, a, you, to, of, it, and in) in the phoneticallytranscribed...

Dialog act modelling for conversational speech (1998)

Stolcke, Andreas, Shriberg, Elizabeth, Bates, Rebecca, Coccaro, Noah, Jurafsky, Daniel, Martin, Rachel, ...

We describe an integrated approach for statistical modeling of discourse structure for natural conversational speech. Our model is based on 42 'dialog acts’ (e.g., Statement, Question, Backchannel,...

Can Prosody Aid the Automatic Classification of Dialog Acts in Conversational Speech? (1998)

Shriberg, Elizabeth, Bates, Rebecca, Taylor, Paul, Stolcke, Andreas, Jurafsky, Daniel, Ries, Klaus, ...

Identifying whether an utterance is a statement, question, greeting, and so forth is integral to effective automatic understanding of natural dialog. Little is known, however, about how such dialog...

Dialog act modelling for conversational speech (1998)

Stolcke, Andreas, Shriberg, Elizabeth, Bates, Rebecca, Coccaro, Noah, Jurafsky, Daniel, Martin, Rachel, ...

We describe an integrated approach for statistical modeling of discourse structure for natural conversational speech. Our model is based on 42 'dialog acts’ (e.g., Statement, Question, Backchannel,...

Can Prosody Aid the Automatic Classification of Dialog Acts in Conversational Speech? (1998)

Shriberg, Elizabeth, Bates, Rebecca, Taylor, Paul, Stolcke, Andreas, Jurafsky, Daniel, Ries, Klaus, ...

Identifying whether an utterance is a statement, question, greeting, and so forth is integral to effective automatic understanding of natural dialog. Little is known, however, about how such dialog...

Lexical, Prosodic, and Syntactic Cues for Dialog Acts (1998)

Daniel Jurafsky, Elizabeth Shribergt, Barbara Fox, Traci Curl

The structure of a discourse is reflected in many as-pects of its linguistic realization, including its lexi-cal, prosodic, syntactic, and semantic nature. Multi-party dialog contains a particular...

Dialog Act Modeling for Conversational Speech (1998)

Andreas Stolcke, Elizabeth Shriberg, Sri International, Noah Coccaro, Daniel Jurafsky, Rachel Martin, ...

We describe an integrated approach for statistical modeling of discourse structure for natural conversational speech. Our model is based on 42 `dialog acts' (e.g., Statement, Question,...

How Verb Subcategorization Frequencies Are Affected By Corpus Choice (1998)

Bayesian Models of Human Sentence Processing (1998)

The probabilistic relation between verbs and their arguments plays an important role in modern statistical parsers and supertaggers, and in psychological theories of language processing. But these...

Srini Narayanan Daniel, Daniel Jurafsky

Human language processing relies on many kinds of linguistic knowledge, and is sensitive to their frequency, including lexical frequencies (Tyler, 1984; Salasoo & Pisoni, 1985; MarslenWilson,...

Reduction Of English Function Words In Switchboard (1998)

Daniel Jurafsky, Alan Bell, Eric Fosler-lussiery, Cynthia Gir, William Raymond

The causes of pronunciation reduction in 8458 occurrences of ten frequent English function words in a four-hour sample from conversations from the Switchboard corpus were examined. Using ordinary...

An American National Corpus: A Proposal (1998)

Charles J. Fillmore, Daniel Jurafsky, Nancy Ide, Catherine Macleod

This paper proposes the development of an American National Corpus comparable to the British National Corpus. Corpus-analytic work has demonstrated that the use of the British National Corpus is...

Bayesian Models of Human Sentence Processing (1998)

Dialog Act Modeling for Conversational Speech (1998)

Human language processing relies on many kinds of linguistic knowledge, and is sensitive to their frequency, including lexical frequencies (Tyler, 1984; Salasoo & Pisoni, 1985; MarslenWilson,...

Andreas Stolcke, Elizabeth Shriberg, Sri International, Noah Coccaro, Daniel Jurafsky, Rachel Martin, ...

We describe an integrated approach for statistical modeling of discourse structure for natural conversational speech. Our model is based on 42 `dialog acts' (statement, question, backchannel,...

Verb Sense and Verb Subcategorization Probabilities (1998)

Towards Better Integration Of Semantic Predictors In Statistical Language Modeling (1998)

this paper we measure these probabilities only for syntactic argument frames, but the Lemma Argument Probability hypothesis bears equally on the semantic/thematic expectations shown by studies such...

Noah Coccaro, Daniel Jurafsky

We introduce a number of techniques designed to help integrate semantic knowledge with N-gram language models for automatic speech recognition. Our techniques allow us to integrate Latent Semantic...

Towards Better Integration Of Semantic Predictors In Statistical Language Modeling (1998)

Noah Coccaro, Daniel Jurafsky

We introduce a number of techniques designed to help integrate semantic knowledge with N-gram language models for automatic speech recognition. Our techniques allow us to integrate Latent Semantic...

Bayesian models of human sentence processing (1998)

Automatic detection of discourse structure for speech recognition and understanding. (1997)

Human language processing relies on many kinds of linguistic knowledge, and is sensitive to their frequency, including lexical

Jurafsky, Daniel, Bates, Rebecca, Coccaro, Noah, Martin, Rachel, Meteer, Marie, Ries, Klaus, ...

We describe a new approach for statistical modeling and detection of discourse structure for natural conversational speech. Our model is based on 42 ‘Dialog Acts’ (DAs), (question, answer,...

Automatic detection of discourse structure for speech recognition and understanding. (1997)

Jurafsky, Daniel, Bates, Rebecca, Coccaro, Noah, Martin, Rachel, Meteer, Marie, Ries, Klaus, ...

We describe a new approach for statistical modeling and detection of discourse structure for natural conversational speech. Our model is based on 42 ‘Dialog Acts’ (DAs), (question, answer,...

Automatic Detection of Discourse Structure for Speech Recognition and Understanding (1997)

Daniel Jurafsky, Elizabeth Shriberg (sri, Andreas Stolcke (sri

We describe a new approach for statistical modeling and detection of discourse structure for natural conversational speech. Our model is based on 42 'Dialog Acts' (DAs), (question, answer,...

Automatic Detection of Discourse Structure for Speech Recognition and Understanding (1997)

Daniel Jurafsky, Rebecca Bates, Noah Coccaro

We describe a new approach for statistical modeling and detection of discourse structure for natural conversational speech. Our model is based on 42 `Utterance Types' (UTs), (question, answer,...

Learning bias and phonological rule induction (1996)

A probabilistic model of lexical and syntactic access and disambiguation (1996)

A fundamental debate in the machine learning of language has been the role of prior knowledge in the learning process. Purely nativist approaches, such as the Principles and Parameters model, build...

Learning Bias and Phonological Rule Induction (1996)

The problems of access-- retrieving linguistic structure from some mental grammar-- and disambiguation-- choosing among these structures to correctly parse ambiguous linguistic input-- are...

Learning bias and phonological rule induction (1996)

this paper we suggest that an alternative to the purely nativist or purely empiricist learning paradigms is to represent the prior knowledge of language as a set of abstract learning biases, which...

Learning bias and phonological-rule induction (1996)

A fundamental debate in the machine learning of language has been the role of prior knowledge in the learning process. Purely nativist approaches, such as the Principles and Parameters model, build...

Learning phonological rule probabilities from speech corpora with exploratory computational phonology (1995)

A fundamental debate in the machine learning of language has been the role of prior knowledge in the learning process. Purely nativist approaches, such as the Principles and Parameters model, build...

Gary Tajchman, Daniel Jurafsky, Eric Fosler

This paper presents an algorithm for learn-ing the probabilities of optional phonolog-ical rules from corpora. The algorithm is based on using a speech recognition sys-tem to discover the surface...

Automatic Induction of Finite State Transducers for Simple Phonological Rules (1995)

Building Multiple Pronunciation Models For Novel Words Using Exploratory Computational Phonology (1995)

This paper presents a method for learning phonological rules from sample pairs of underlying and surface forms, without negative evidence. The learned rules are represented as finite state...

Gary Tajchman, Eric Fosler, Daniel Jurafsky

In this paper we describe a completely automatic algorithm that builds multiple pronunciation word models by expanding baseform pronunciations with a set of candidate phonological rules. We show how...

Using A Stochastic Context-Free Grammar As A Language Model For Speech Recognition (1995)

Daniel Jurafsky, Chuck Wooters, Jonathan Segal, Andreas Stolcke, Eric Fosler, Gary Tajchman, ...

This paper describes a number of experiments in adding new grammatical knowledge to the Berkeley Restaurant Project (BeRP), our medium-vocabulary (1300 word), speaker-independent, spontaneous...

Learning Phonological Rule Probabilities from Speech Corpora with Exploratory Computational Phonology (1995)

Gary Tajchman, Daniel Jurafsky, And Eric Fosler, Eric Fosler

this paper, we employ techniques from speech recognition research to address the problem of assigning probabilities to these optional phonological rules. We introduce a completely automatic algorithm...

Type Underspecification and On-line Type Construction in the Lexicon (1994)

Jean-pierre Koenig, Daniel Jurafsky

This paper focuses on this second proposal, called ON-LINE TYPE CONSTRUCTION.

Integrating Experimental Models of Syntax, Phonology, and Accent/Dialect in a Speech Recognizer (1994)

Daniel Jurafsky, Chuck Wooters, Gary Tajchman, Jonathan Segal, Andreas Stolcke, Nelson Morgan

This paper describes three preliminary experiments in adding new language knowledge to the recognizer BeRP:

Automatic Induction of Finite State Transducers for Simple Phonological Rules (1994)

The Berkeley Restaurant Project (1994)

This paper presents a method for learning phonological rules from sample pairs of underlying and surface forms, without negative evidence. The learned rules are represented as finite state...

Daniel Jurafsky, Chuck Wooters, Gary Tajchman, Jonathan Segal, Andreas Stolcke, Eric Fosler, ...

This paper describes the architecture and performance of the Berkeley Restaurant Project (BeRP), a medium-vocabulary, speaker-independent, spontaneous continuous speech understanding system currently...

Integrating experimental models of syntax, phonology, and accent/dialect in a speech recognizer. An investigation of tightly coupled time synchronous speech (1994)

Daniel Jurafsky, Chuck Wooters, Jonathan Segal, Andreas Stolcke, Nelson Morgan

As the field of speech understanding matures, and particularly as the quality of front-end and phonetic components improves, researchers have begun to explore ways to add new kinds of language...

A Cognitive Model of Sentence Interpretation: the Construction Grammar approach (1993)

A cognitive model of sentence interpretation: The construction grammar approach (1993)

This paper describes a new, psychologically-plausible model of human sentence interpretation, based on a new model of linguistic structure, Construction Grammar. This on-line, parallel, probabilistic...

How Verb Subcategorization Frequencies are Affected by Corpus Choice

This paper describes a new, psychologically-plausible model of human sentence interpretation, based on a new model of linguistic structure, Construction Grammar. This on-line, parallel, probabilistic...

Automatic Induction of Finite State Transducers for Simple Phonological Rules

Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech

Andreas Stolcke, Noah Coccaro, Rebecca Bates, Paul Taylor, Klaus Ries, ...

Learning Bias and Phonological-Rule Induction