Directional adposition use in English, Swedish and Finnish

Directional adpositions such as to the left of describe where a Figure is in relation to a Ground. English and Swedish directional adpositions refer to the location of a Figure in relation to a Ground, whether both are static or in motion. In contrast, the Finnish directional adpositions edellä (in front of) and jäljessä (behind) solely describe the location of a moving Figure in relation to a moving Ground (Nikanne, 2003). When using directional adpositions, a frame of reference must be assumed for interpreting the meaning of directional adpositions. For example, the meaning of to the left of in English can be based on a relative (speaker or listener based) reference frame or an intrinsic (object based) reference frame (Levinson, 1996). When a Figure and a Ground are both in motion, it is possible for a Figure to be described as being behind or in front of the Ground, even if neither have intrinsic features. As shown by Walker (in preparation), there are good reasons to assume that in the latter case a motion based reference frame is involved. This means that if Finnish speakers would use edellä (in front of) and jäljessä (behind) more frequently in situations where both the Figure and Ground are in motion, a difference in reference frame use between Finnish on one hand and English and Swedish on the other could be expected. We asked native English, Swedish and Finnish speakers’ to select adpositions from a language specific list to describe the location of a Figure relative to a Ground when both were shown to be moving on a computer screen. We were interested in any differences between Finnish, English and Swedish speakers. All languages showed a predominant use of directional spatial adpositions referring to the lexical concepts TO THE LEFT OF, TO THE RIGHT OF, ABOVE and BELOW. There were no differences between the languages in directional adpositions use or reference frame use, including reference frame use based on motion. We conclude that despite differences in the grammars of the languages involved, and potential differences in reference frame system use, the three languages investigated encode Figure location in relation to Ground location in a similar way when both are in motion. Levinson, S. C. (1996). Frames of reference and Molyneux’s question: Crosslingiuistic evidence. In P. Bloom, M.A. Peterson, L. Nadel & M.F. Garrett (Eds.) Language and Space (pp.109-170). Massachusetts: MIT Press. Nikanne, U. (2003). How Finnish postpositions see the axis system. In E. van der Zee & J. Slack (Eds.), Representing direction in language and space. Oxford, UK: Oxford University Press. Walker, C. (in preparation). Motion encoding in language, the use of spatial locatives in a motion context. Unpublished doctoral dissertation, University of Lincoln, Lincoln. United Kingdo

Dysfluencies as intra-utterance dialogue moves

Ginzburg J, Fernández R, Schlangen D. Dysfluencies as intra-utterance dialogue moves. Semantics and Pragmatics. 2014;7

The Multidimensionality of Second Language Oral Fluency:Interfacing Cognitive Fluency and Utterance Fluency

The current study examined the extent to which cognitive fluency (CF) contributes to utterance fluency (UF) at the level of constructs. A total of 128 Japanese-speaking learners of English completed four speaking tasks—argumentative task, picture narrative task, reading-to-speaking task, and reading-while-listening-to-speaking task—and a battery of linguistic knowledge tests, capturing vocabulary size, lexical retrieval speed, sentence construction skills, grammaticality judgements, and articulatory speed. Their speaking performance was analyzed in terms of speed, breakdown, and repair fluency (i.e., UF), and scores on linguistic knowledge tests were used to assess students’ L2 linguistic resources and processing skills (i.e., CF). Structural equation modelling revealed a complex interplay between the multidimensionality of CF and UF and speaking task types. L2 processing speed consistently contributed to all aspects of UF across speaking tasks, whereas the role of linguistic resources in speed and repair fluency varied, depending on task characteristics

The Distribution Of Disfluencies In Spontaneous Speech: Empirical Observations And Theoretical Implications

This dissertation provides an empirical description of the forms and their distribution of disfluencies in spontaneous speech. Although research in this area has received much attention in past four decades, large scale analyses of speech corpora from multiple communication settings, languages, and speaker\u27s cognitive states are still lacking. Understandings of regularities of different kinds of disfluencies based on large speech samples across multiple domains are essential for both theoretical and applied purposes. As an attempt to fill this gap, this dissertation takes the approach of quantitative analysis of large corpora of spontaneous speech. The selected corpora reflect a diverse range of tasks and languages. The dissertation re-examines speech disfluency phenomena, including silent pauses, filled pauses (``um and ``uh ) and repetitions, and provides the empirical basis for future work in both theoretical and applied settings. Results from the study of silent and filled pauses indicate that a potential sociolinguistic variation can in fact be explained from the perspective of the speech planning process. The descriptive analysis of repetitions has identified a new form of repetitive phenomenon: repetitive interpolation. Both the acoustic and textual properties of repetitive interpolation have been documented through rigorous quantitative analysis. The defining features of this phenomenon can be further used in designing speech based applications such as speaker state detection. Although the goal of this descriptive analysis is not to formulate and test specific hypothesis about speech production, potential directions for future research in speech production models are proposed and evaluated. The quantitative methods employed throughout this dissertation can also be further developed into interpretable features in machine learning systems that require automatic processing of spontaneous speech

The Distribution Of Disfluencies In Spontaneous Speech: Empirical Observations And Theoretical Implications

This dissertation provides an empirical description of the forms and their distribution of disfluencies in spontaneous speech. Although research in this area has received much attention in past four decades, large scale analyses of speech corpora from multiple communication settings, languages, and speaker\u27s cognitive states are still lacking. Understandings of regularities of different kinds of disfluencies based on large speech samples across multiple domains are essential for both theoretical and applied purposes. As an attempt to fill this gap, this dissertation takes the approach of quantitative analysis of large corpora of spontaneous speech. The selected corpora reflect a diverse range of tasks and languages. The dissertation re-examines speech disfluency phenomena, including silent pauses, filled pauses (``um and ``uh ) and repetitions, and provides the empirical basis for future work in both theoretical and applied settings. Results from the study of silent and filled pauses indicate that a potential sociolinguistic variation can in fact be explained from the perspective of the speech planning process. The descriptive analysis of repetitions has identified a new form of repetitive phenomenon: repetitive interpolation. Both the acoustic and textual properties of repetitive interpolation have been documented through rigorous quantitative analysis. The defining features of this phenomenon can be further used in designing speech based applications such as speaker state detection. Although the goal of this descriptive analysis is not to formulate and test specific hypothesis about speech production, potential directions for future research in speech production models are proposed and evaluated. The quantitative methods employed throughout this dissertation can also be further developed into interpretable features in machine learning systems that require automatic processing of spontaneous speech

Psycholinguistics in Fluency Disorders: Prearticulatory Speech Planning In Stuttering and Cluttering

The Covert Repair Hypothesis (CRH) is an account for speech errors in normally fluent speakers, and also hypothesizes errors in the phonological encoding stage in people who stutter (PWS). Previous research has shown that PWS exhibit poorer performance compared to typically fluent adults (TFA) on linguistic tasks designed to tap into the level of phonological encoding, such as phoneme monitoring. Stuttering and cluttering often co-occur, thus the field can benefit from extending this methodology to study people who clutter (PWC). Experiment 1 in Chapter 2 used phoneme monitoring to study phonological encoding in PWS and PWC, with three conclusions: (1) slower performance by PWS; (2) increased errors by PWS compared to TFA; and (3) similar performance by PWC compared to TFA, suggesting that PWC do not exhibit difficultly with phonological encoding at the single word level. One criticism of the CRH is that the cause of errors in the speech plan has not been accounted for. Chapter 3 proposed the Near Neighbor Interference Hypothesis (NNIH) as an account for errors in the speech plan in PWS, which hypothesizes that due to a lifetime of word-substitution behavior to avoid stuttering, semantic neighborhoods of PWS may be organized differently than TFA, with more neighbors and/or stronger connections between neighbors. Chapter 3 tested the NNIH by investigating the effects of the number of associates (NoA) and the degree of relatedness on performance during lexical decision. Previous research shows TFA respond faster to words with a high vs. low NoA, and words preceded by a picture with a high vs. a low degree of relatedness. Following from the NNIH, it was hypothesized that the magnitude of these effects would be greater in PWS. In Experiment 2, both groups responded faster to words with higher NoA, but PWS were slower to respond than TFA overall, regardless of NoA. In Experiment 3, PWS were not overall slower than TFA, and the effect of degree of relatedness was actually stronger for TFA than PWS. Together, these results suggest that rather than experiencing a benefit from more semantic neighbors, it appears PWS may experience interference from these additional neighbors. Overall, results suggest that PWS may have errors in their speech plan that originate prearticulatoraily, potentially at the lexical-semantic level, and are passed down to the phonological encoding level

Identification and correction of speech repairs in the context of an automatic speech recognition system

Recent advances in automatic speech recognition systems for read (dictated) speech have led researchers to confront the problem of recognising more spontaneous speech. A number of problems, such as disfluencies, appear when read speech is replaced with spontaneous speech. In this work we deal specifically with what we class as speech-repairs. Most disfluency processes deal with speech-repairs at the sentence level. This is too late in the process of speech understanding. Speech recognition systems have problems recognising speech containing speech-repairs. The approach taken in this work is to deal with speech-repairs during the recognition process. Through an analysis of spontaneous speech the grammatical structure of speech- repairs was identified as a possible source of information. It is this grammatical structure, along with some pattern matching to eliminate false positives, that is used in the approach taken in this work. These repair structures are identified within a word lattice and when found result in a SKIP being added to the lattice to allow the reparandum of the repair to be ignored during the hypothesis generation process. Word fragment information is included using a sub-word pattern matching process and cue phrases are also identified within the lattice and used in the repair detection process. These simple, yet effective, techniques have proved very successful in identifying and correcting speech-repairs in a number of evaluations performed on a speech recognition system incorporating the repair procedure. On an un-seen spontaneous lecture taken from the Durham corpus, using a dictionary of 2,275 words and phoneme corruption of 15%, the system achieved a correction recall rate of 72% and a correction precision rate of 75%.The achievements of the project include the automatic detection and correction of speech-repairs, including word fragments and cue phrases, in the sub-section of an automatic speech recognition system processing spontaneous speech