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We apply a decision tree based approach to pronoun resolution in spoken dialogue. Our system deals with pronouns with NP- and non-NP-antecedents. We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features. We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron’s (2002) manually tuned system.
We present an implemented machine learning system for the automatic detection of nonreferential it in spoken dialog. The system builds on shallow features extracted from dialog transcripts. Our experiments indicate a level of performance that makes the system usable as a preprocessing filter for a coreference resolution system. We also report results of an annotation study dealing with the classification of it by naive subjects.
In this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken multi-party dialog. Manual inspection of the two knowledge sources showed that, with some interesting exceptions, Wikipedia is superior to WordNet when it comes to the coverage of information necessary to resolve the bridging anaphors in our data set. We further describe a simple procedure for the automatic extraction of the required knowledge from Wikipedia by means of an API, and discuss some of the implications of the procedure’s performance.
Online Access Tools for Spoken German: The Resources of the Deutsches Spracharchiv in a Database
(2002)
This paper shows some details of the modernization of the Deutsches Spracharchiv (DSAv). It explores some future possibilities of linguistical documentation and analysis using the Web. The Institut für Deutsche Sprache (IDS) in Mannheim is the central institution for linguistic research in Germany. The DSAv in the IDS is the center for documentation and research of spoken German. These archives include the largest collection of sound recordings of spoken German (dialects and colloquial speech, including e.g. lots of extinct dialects of former German territories in Eastern Europe) - altogether more than 15,000 sound recordings. The lacking clarification and accessibility of this data material has been felt as an essential deficit. The opportunity to edit the sound signal digitally offers a much easier access to spoken language. Through the integration of the already existing information about the corpora and the transcribed texts in an information- and full text databank, as well as the linking of the data with the acoustic signal (alignment), arises a data-pool with considerably better documentation of the materials and a fast direct grasp of the recorded sounds. Thus, the DSAv initiates totally new research questions for the work at the IDS, as well as for linguistics altogether.
This paper presents an extension to the Stuttgart-Tübingen TagSet, the standard part-of-speech tag set for German, for the annotation of spoken language. The additional tags deal with hesitations, backchannel signals, interruptions, onomatopoeia and uninterpretable material. They allow one to capture phenomena specific to spoken language while, at the same time, preserving inter-operability with already existing corpora of written language.
We present the annotation of information structure in the MULI project. To learn more about the information structuring means in prosody, syntax and discourse, theory- independent features were defined for each level. We describe the features and illustrate them on an example sentence. To investigate the interplay of features, the representation has to allow for inspecting all three layers at the same time. This is realised by a stand-off XML mark-up with the word as the basic unit. The theory-neutral XML stand-off annotation allows integrating this resource with other linguistic resources such as the Tiger Treebank for German or the Penn treebank for English.
We present an XML-based metadata standard for the documentation of speech and multimedia corpora that was developed at the Institute for German Language (IDS) in Mannheim, Germany. The IDS is one of the major institutions providing German speech and language corpora to researchers. These corpora stem from many different sources and were previously documented in a rather heterogeneous fashion using a variety of data models and formats. In order to unify the documentation for existing and future corpora, the IDS- internal Archive for Spoken German collaborated with several projects and developed a set of standardised XML metadata schemas. These XML schemas build on existing internal and external documentation schemas (such as IMDI) and take into account the workflow of speech corpus production. In order to minimise redundancy, separate schemas were designed for projects, speakers, recording sessions, and entire corpora. The resulting schemas are tested in ongoing speech and multi-media projects at the IDS and are regularly revised. They are accompanied by element definitions, guidelines, and examples. In addition, a mapping to IMDI will be provided.
The metadata management system for speech corpora “memasysco” has been developed at the Institut für Deutsche Sprache (IDS) and is applied for the first time to document the speech corpus “German Today”. memasysco is based on a data model for the documentation of speech corpora and contains two generic XML schemas that drive data capture, XML native database storage, dynamic publishing, and information retrieval. The development of memasysco’s information architecture was mainly based on the ISLE MetaData Initiative (IMDI) guidelines for publishing metadata of linguistic resources. However, since we also have to support the corpus management process in research projects at the IDS, we need a finer atomic granularity for some documentation components as well as more restrictive categories to ensure data integrity. The XML metadata of different speech corpus projects are centrally validated and natively stored in an Oracle XML database. The extension of the system to the management of annotations of audio and video signals (e.g. orthographic and phonetic transcriptions) is planned for the near future.
Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of all linguistic theories that take social interaction involving language into account. However, determining communicative functions is a notoriously difficult task both for human interpreters and systems. It involves an interpretative process that integrates various sources of information. Existing work on communicative function classification comes from either dialogue act tagging where it is generally coarse grained concerning the feed- back phenomena or it is token-based and does not address the variety of forms that feed- back utterances can take. This paper introduces an annotation framework, the dataset and the related annotation campaign (involving 7 raters to annotate nearly 6000 utterances). We present its evaluation not merely in terms of inter-rater agreement but also in terms of usability of the resulting reference dataset both from a linguistic research perspective and from a more applicative viewpoint.
The current paper presents a corpus containing 35 dialogues of spontaneously spoken southern German, including half an hour of articulography for 13 of the speakers. Speakers were seated in separate recording chambers, mimicking a telephone call, and recorded on individual audio channels. The corpus provides manually corrected word boundaries and automatically aligned segment boundaries. Annotations are provided in the Praat format. In addition to audio recordings, speakers filled out a detailed questionnaire, assessing among others their audio-visual consumption habits.
Ph@ttSessionz and Deutsch heute are two large German speech databases. They were created for different purposes: Ph@ttSessionz to test Internet-based recordings and to adapt speech recognizers to the voices of adolescent speakers, Deutsch heute to document regional variation of German. The databases differ in their recording technique, the selection of recording locations and speakers, elicitation mode, and data processing.
In this paper, we outline how the recordings were performed, how the data was processed and annotated, and how the two databases were imported into a single relational database system. We present acoustical measurements on the digit items of both databases. Our results confirm that the elicitation technique affects the speech produced, that f0 is quite comparable despite different recording procedures, and that large speech technology databases with suitable metadata may well be used for the analysis of regional variation of speech.
Designing a Bilingual Speech Corpus for French and German Language Learners: a Two-Step Process
(2014)
We present the design of a corpus of native and non-native speech for the language pair French-German, with a special emphasis on phonetic and prosodic aspects. To our knowledge there is no suitable corpus, in terms of size and coverage, currently available for the target language pair. To select the target L1-L2 interference phenomena we prepare a small preliminary corpus (corpus1), which is analyzed for coverage and cross-checked jointly by French and German experts. Based on this analysis, target phenomena on the phonetic and phonological level are selected on the basis of the expected degree of deviation from the native performance and the frequency of occurrence. 14 speakers performed both L2 (either French or German) and L1 material (either German or French). This allowed us to test, recordings duration, recordings material, the performance of our automatic aligner software. Then, we built corpus2 taking into account what we learned about corpus1. The aims are the same but we adapted speech material to avoid too long recording sessions. 100 speakers will be recorded. The corpus (corpus1 and corpus2) will be prepared as a searchable database, available for the scientific community after completion of the project.
The IFCASL corpus is a French-German bilingual phonetic learner corpus designed, recorded and annotated in a project on individualized feedback in computer-assisted spoken language learning. The motivation for setting up this corpus was that there is no phonetically annotated and segmented corpus for this language pair of comparable of size and coverage. In contrast to most learner corpora, the IFCASL corpus incorporate data for a language pair in both directions, i.e. in our case French learners of German, and German learners of French. In addition, the corpus is complemented by two sub-corpora of native speech by the same speakers. The corpus provides spoken data by about 100 speakers with comparable productions, annotated and segmented on the word and the phone level, with more than 50% manually corrected data. The paper reports on inter-annotator agreement and the optimization of the acoustic models for forced speech-text alignment in exercises for computer-assisted pronunciation training. Example studies based on the corpus data with a phonetic focus include topics such as the realization of /h/ and glottal stop, final devoicing of obstruents, vowel quantity and quality, pitch range, and tempo.
The aim of this paper is to highlight the actual need for corpora that have been annotated based on acoustic information. The acoustic information should be coded in features or properties and is needed to inform further processing systems, i.e. to present a basis for a speech recognition system using linguistic information. Feature annotation of existing corpora in combination with segmental annotation can provide a powerful training material for speech recognition systems, but will as well challenge the further processing of features to segments and syllables. We present here the theoretical preliminaries for our multilingual feature extraction system, that we are currently working on.
This paper presents the first release of the KiezDeutsch Korpus (KiDKo), a new language resource with multiparty spoken dialogues of Kiezdeutsch, a newly emerging language variety spoken by adolescents from multi-ethnic urban areas in Germany. The first release of the corpus includes the transcriptions of the data as well as a normalisation layer and part-of-speech annotations. In the paper, we describe the main features of the new resource and then focus on automatic POS tagging of informal spoken language. Our tagger achieves an accuracy of nearly 97% on KiDKo. While we did not succeed in further improving the tagger using ensemble tagging, we present our approach to using the tagger ensembles for identifying error patterns in the automatically tagged data.
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks
(2016)
In discourse relation annotation, there is currently a variety of different frameworks being used, and most of them have been developed and employed mostly on written data. This raises a number of questions regarding interoperability of discourse relation annotation schemes, as well as regarding differences in discourse annotation for written vs. spoken domains. In this paper, we describe ouron annotating two spoken domains from the SPICE Ireland corpus (telephone conversations and broadcast interviews) according todifferent discourse annotation schemes, PDTB 3.0 and CCR. We show that annotations in the two schemes can largely be mappedone another, and discuss differences in operationalisations of discourse relation schemes which present a challenge to automatic mapping. We also observe systematic differences in the prevalence of implicit discourse relations in spoken data compared to written texts,find that there are also differences in the types of causal relations between the domains. Finally, we find that PDTB 3.0 addresses many shortcomings of PDTB 2.0 wrt. the annotation of spoken discourse, and suggest further extensions. The new corpus has roughly theof the CoNLL 2015 Shared Task test set, and we hence hope that it will be a valuable resource for the evaluation of automatic discourse relation labellers.
There have been several attempts to annotate communicative functions to utterances of verbal feedback in English previously. Here, we suggest an annotation scheme for verbal and non-verbal feedback utterances in French including the categories base, attitude, previous and visual. The data comprises conversations, maptasks and negotiations from which we extracted ca. 13,000 candidate feedback utterances and gestures. 12 students were recruited for the annotation campaign of ca. 9,500 instances. Each instance was annotated by between 2 and 7 raters. The evaluation of the annotation agreement resulted in an average best-pair kappa of 0.6. While the base category with the values acknowledgement, evaluation, answer, elicit and other achieves good agreement, this is not the case for the other main categories. The data sets, which also include automatic extractions of lexical, positional and acoustic features, are freely available and will further be used for machine learning classification experiments to analyse the form-function relationship of feedback.