人教版高中英语新课程教材中,语言运用（Using Language）是每个单元必不可少的部分,提供了围绕单元中心话题的听、说、读、写的综合性练习,是单元中心话题的延续和升华.如何设计Using Language部分的教学,使自己的教学模式既不落俗套,又能真正体现新课程标准所倡导的教学理念,正是广大一线英语教师一直努力探索的问题.

打磨Using Language,倡导新理念

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The Syntax‐Phonology Interface

Redundancy and reduction: Speakers manage syntactic information density

The core niche for language use is in verbal interaction, involving the rapid exchange of turns at talking. This paper reviews the extensive literature about this system, adding new statistical analyses of behavioural data where they have been missing, demonstrating that turn-taking has the systematic properties originally noted by Sacks, Schegloff and Jefferson (1974; hereafter SSJ). This system poses some significant puzzles for current theories of language processing: the gaps between turns are short (of the order of 200 ms), but the latencies involved in language production are much longer (over 600 ms). This seems to imply that participants in conversation must predict (or ‘project’ as SSJ have it) the end of the current speaker’s turn in order to prepare their response in advance. This in turn implies some overlap between production and comprehension despite their use of common processing resources. Collecting together what is known behaviourally and experimentally about the system, the space for systematic explanations of language processing for conversation can be significantly narrowed, and we sketch some first model of the mental processes involved for the participant preparing to speak next.

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Timing in turn-taking and its implications for processing models of language

The World Wide Web contains a significant amount of information expressed using natural language. While unstructured text is often difficult for machines to understand, the field of Information Extraction (IE) offers a way to map textual content into a structured knowledge base. The ability to amass vast quantities of information from Web pages has the potential to increase the power with which a modern search engine can answer complex queries. 
IE has traditionally focused on acquiring knowledge about particular relationships within a small collection of domain-specific text. Typically, a target relation is provided to the system as input along with extraction patterns or examples that have been specified by hand. Shifting to a new relation requires a person to create new patterns or examples. This manual labor scales linearly with the number of relations of interest. 
The task of extracting information from the Web presents several challenges for existing IE systems. The Web is large and heterogeneous; the number of potentially interesting relations is massive and their identity often unknown. To enable large-scale knowledge acquisition from the Web, this thesis presents Open Information Extraction, a novel extraction paradigm that automatically discovers thousands of relations from unstructured text and readily scales to the size and diversity of the Web.

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Open information extraction for the web

This paper describes a recently completed common resource for the study of spoken discourse, the NXT-format Switchboard Corpus. Switchboard is a long-standing corpus of telephone conversations (Godfrey et al. in SWITCHBOARD: Telephone speech corpus for research and development. In Proceedings of ICASSP-92, pp. 517---520, 1992). We have brought together transcriptions with existing annotations for syntax, disfluency, speech acts, animacy, information status, coreference, and prosody; along with substantial new annotations of focus/contrast, more prosody, syllables and phones. The combined corpus uses the format of the NITE XML Toolkit, which allows these annotations to be browsed and searched as a coherent set (Carletta et al. in Lang Resour Eval J 39(4):313---334, 2005). The resulting corpus is a rich resource for the investigation of the linguistic features of dialogue and how they interact. As well as describing the corpus itself, we discuss our approach to overcoming issues involved in such a data integration project, relevant to both users of the corpus and others in the language resource community undertaking similar projects.

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The NXT-format Switchboard Corpus: a rich resource for investigating the syntax, semantics, pragmatics and prosody of dialogue

This article introduces a new way to explain how information structure is signaled prosodically in English. I claim that METRICAL STRUCTURE plays a central role (Ladd 2008, Truckenbrodt 1995). Information structure (defined as in Steedman 1991 and Vallduvi & Vilkuna 1998) places strong constraints on the PROBABIILISTIC mapping of words onto metrical prosodic structure—that is, foci usually align with nuclear accents and theme/rheme units with prosodic phrases, and themes are less metrically prominent than rhemes. It is shown that focus position, scope, and pragmatic interpretation are then derived by manipulating EXPECTED PROMINENCE within metrical structure. Broadly, the more prominent a word than expected, the more likely a contrastive reading; the less prominent, the more likely a givenness reading. Both constructed and naturally occurring examples from the Switchboard corpus are used.

The centrality of metrical structure in signaling information structure: A probabilistic perspective

This work concerns how information structure is signalled prosodically in English, that is, how prosodic prominence and phrasing are used to indicate the salience and organisation of information in relation to a discourse model. It has been standardly held that information structure is primarily signalled by the distribution of pitch accents within syntax structure, as well as intonation event type. However, we argue that these claims underestimate the importance, and richness, of metrical prosodic structure and its role in signalling information structure. We advance a new theory, that information structure is a strong constraint on the mapping of words onto metrical prosodic structure. We show that focus (kontrast) aligns with nuclear prominence, while other accents are not usually directly 'meaningful'. Information units (theme/rheme) try to align with prosodic phrases. This mapping is probabilistic, so it is also influenced by lexical and syntactic effects, as well as rhythmical constraints and other features including emphasis. Rather than being directly signalled by the prosody, the likelihood of each information structure interpretation is mediated by all these properties. We demonstrate that this theory resolves problematic facts about accent distribution in earlier accounts and makes syntactic focus projection rules unnecessary. Previous theories have claimed that contrastive accents are marked by a categorically distinct accent type to other focal accents (e.g. L+H* v H*). We show this distinction in fact involves two separate semantic properties: contrastiveness and theme/rheme status. Contrastiveness is marked by increased prominence in general. Themes are distinguished from rhemes by relative prominence, i.e. the rheme kontrast aligns with nuclear prominence at the level of phrasing that includes both theme and rheme units. In a series of production and perception experiments, we directly test our theory against previous accounts, showing that the only consistent cue to the distinction between theme and rheme nuclear accents is relative pitch height. This height difference accords with our understanding of the marking of nuclear prominence: theme peaks are only lower than rheme peaks in rheme-theme order, consistent with post-nuclear lowering; in theme-rheme order, the last of equal peaks is perceived as nuclear. The rest of the thesis involves analysis of a portion of the Switchboard corpus which we have annotated with substantial new layers of semantic (kontrast) and prosodic features, which are described. This work is an essentially novel approach to testing discourse semantics theories in speech. Using multiple regression analysis, we demonstrate distributional properties of the corpus consistent with our claims. Plain and nuclear accents are best distinguished by phrasal features, showing the strong constraint of phrase structure on the perception of prominence. Nuclear accents can be reliably predicted by semantic/syntactic features, particularly kontrast, while other accents cannot. Plain accents can only be identified well by acoustic features, showing their appearance is linked to rhythmical and low-level semantic features. We further show that kontrast is not only more likely in nuclear position, but also if a word is more structurally or acoustically prominent than expected given its syntactic/information status properties. Consistent with our claim that nuclear accents are distinctive, we show that pre-, postand nuclear accents have different acoustic profiles; and that the acoustic correlates of increased prominence vary by accent type, i.e. pre-nuclear or nuclear. Finally, we demonstrate the efficacy of our theory compared to previous accounts using examples from the corpus.

Information structure and the prosodic structure of English : a probabilistic relationship

The immense prosodic variation of natural conversational speech makes it challenging to predict which words are prosodically prominent in this genre. In this paper, we examine a new feature, accent ratio, which captures how likely it is that a word will be realized as prominent or not. We compare this feature with traditional accentprediction features (based on part of speech and N -grams) as well as with several linguistically motivated and manually labeled information structure features, such as whether a word is given, new, or contrastive. Our results show that the linguistic features do not lead to significant improvements, while accent ratio alone can yield prediction performance almost as good as the combination of any other subset of features. Moreover, this feature is useful even across genres; an accent-ratio classifier trained only on conversational speech predicts prominence with high accuracy in broadcast news. Our results suggest that carefully chosen lexicalized features can outperform less fine-grained features.

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To Memorize or to Predict: Prominence labeling in Conversational Speech

We present a framework for the integrated analysis of the textual and prosodic characteristics of information structure in the Switchboard corpus of conversational English. Information structure describes the availability, organisation and salience of entities in a discourse model. We present standards for the annotation of information status (old, mediated and new), and give guidelines for annotating information structure, i.e. theme/rheme and back-ground/kontrast. We show that information structure in English can only be analysed concurrently with prosodic prominence and phrasing. This annotation, using stand-off XML in NXT, can help establish standards for the annotation of information structure in discourse.

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Sasha Calhoun

Papers

The NXT-format Switchboard Corpus: a rich resource for investigating the syntax, semantics, pragmatics and prosody of dialogue

The centrality of metrical structure in signaling information structure: A probabilistic perspective

Information structure and the prosodic structure of English : a probabilistic relationship

To Memorize or to Predict: Prominence labeling in Conversational Speech

A Framework for Annotating Information Structure in Discourse