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Die Darstellung von und Arbeit mit Transkripten spielt in vielen forschungs- und anwendungsbezogenen Arbeiten mit Daten gesprochener Sprache eine wichtige Rolle. Der im ZuMult-Projekt entwickelte Prototyp ZuViel (Zugang zu Visualisierung von Transkripten) knüpft an etablierte Verfahren zur Transkriptdarstellung an und erweitert diese durch neue Möglichkeiten des interaktiven Arbeitens mit Transkripten im digitalen Medium. Der Beitrag führt in diese neuen Möglichkeiten ein und erklärt, wie sie in didaktischen DaF/DaZ-Kontexten aber auch hinsichtlich forschungsbezogener Perspektiven angewendet werden können
Im vorliegenden Artikel wird ein Überblick über das von der DFG geförderte Projekt Zugänge zu multimodalen Korpora gesprochener Sprache – Vernetzung und zielgruppenspezifische Ausdifferenzierung (ZuMult) gegeben. Dabei wird zunächst auf die Sprachdaten und auf die technische Basis der Applikationen eingegangen, die dem Projekt zugrunde liegen. Im Anschluss werden die weiteren Beiträge in diesem Themenheft von KorDaF kurz vorgestellt. Übergeordnetes Thema von ZuMult ist die Verbesserung der Zugänglichkeit von digitalen mündlichen Sprachdaten für verschiedene Anwendungen und Zielgruppen, wobei der Fokus dieses Themenhefts auf Applikationen und Anwender:innen aus der Fremdsprachendidaktik und der DaF-/DaZ-Forschung und -Lehre liegt. Die einzelnen Beiträge beleuchten zentrale methodische und/oder technische Aspekte dieses Themas und beschreiben die Architektur und verschiedene prototypische Anwendungen, die das Projekt entwickelt hat.
As a part of the ZuMult-project, we are currently modelling a backend architecture that should provide query access to corpora from the Archive of Spoken German (AGD) at the Leibniz-Institute for the German Language (IDS). We are exploring how to reuse existing search engine frameworks providing full text indices and allowing to query corpora by one of the corpus query languages (QLs) established and actively used in the corpus research community. For this purpose, we tested MTAS - an open source Lucene-based search engine for querying on text with multilevel annotations. We applied MTAS on three oral corpora stored in the TEI-based ISO standard for transcriptions of spoken language (ISO 24624:2016). These corpora differ from the corpus data that MTAS was developed for, because they include interactions with two and more speakers and are enriched, inter alia, with timeline-based annotations. In this contribution, we report our test results and address issues that arise when search frameworks originally developed for querying written corpora are being transferred into the field of spoken language.
The newest generation of speech technology caused a huge increase of audio-visual data nowadays being enhanced with orthographic transcripts such as in automatic subtitling in online platforms. Research data centers and archives contain a range of new and historical data, which are currently only partially transcribed and therefore only partially accessible for systematic querying. Automatic Speech Recognition (ASR) is one option of making that data accessible. This paper tests the usability of a state-of-the-art ASR-System on a historical (from the 1960s), but regionally balanced corpus of spoken German, and a relatively new corpus (from 2012) recorded in a narrow area. We observed a regional bias of the ASR-System with higher recognition scores for the north of Germany vs. lower scores for the south. A detailed analysis of the narrow region data revealed – despite relatively high ASR-confidence – some specific word errors due to a lack of regional adaptation. These findings need to be considered in decisions on further data processing and the curation of corpora, e.g. correcting transcripts or transcribing from scratch. Such geography-dependent analyses can also have the potential for ASR-development to make targeted data selection for training/adaptation and to increase the sensitivity towards varieties of pluricentric languages.
The newest generation of speech technology caused a huge increase of audio-visual data nowadays being enhanced with orthographic transcripts such as in automatic subtitling in online platforms. Research data centers and archives contain a range of new and historical data, which are currently only partially transcribed and therefore only partially accessible for systematic querying. Automatic Speech Recognition (ASR) is one option of making that data accessible. This paper tests the usability of a state-of-the-art ASR-System on a historical (from the 1960s), but regionally balanced corpus of spoken German, and a relatively new corpus (from 2012) recorded in a narrow area. We observed a regional bias of the ASR-System with higher recognition scores for the north of Germany vs. lower scores for the south. A detailed analysis of the narrow region data revealed – despite relatively high ASR-confidence – some specific word errors due to a lack of regional adaptation. These findings need to be considered in decisions on further data processing and the curation of corpora, e.g. correcting transcripts or transcribing from scratch. Such geography-dependent analyses can also have the potential for ASR-development to make targeted data selection for training/adaptation and to increase the sensitivity towards varieties of pluricentric languages.
Researchers interested in the sounds of speech or the physical gestures of Speakers make use of audio and video recordings in their work. Annotating these recordings presents a different set of requirements to the annotation of text. Special purpose tools have been developed to display video and audio Signals and to allow the creation of time-aligned annotations. This chapter reviews the most widely used of these tools for both manual and automatic generation of annotations on multimodal data.
This paper describes the TEI-based ISO standard 2462:2016 “Transcription of spoken language” and other formats used within CLARIN for spoken language resources. It assesses the current state of support for the standard and the interoperability between these formats and with relevant tools and services. The main idea behind the paper is that a digital infrastructure providing language resources and services to researchers should also allow the combined use of resources and/or services from different contexts. This requires syntactic and semantic interoperability. We propose a solution based on the ISO/TEI format and describe the necessary steps for this format to work as an exchange format with basic semantic interoperability for spoken language resources across the CLARIN infrastructure and beyond.
This paper describes the TEI-based ISO standard 24624:2016 ‘Transcription of spoken language’ and other formats used within CLARIN for spoken language resources. It assesses the current state of support for the standard and the interoperability between these formats and with rele- vant tools and services. The main idea behind the paper is that a digital infrastructure providing language resources and services to researchers should also allow the combined use of resources and/or services from different contexts. This requires syntactic and semantic interoperability. We propose a solution based on the ISO/TEI format and describe the necessary steps for this format to work as an exchange format with basic semantic interoperability for spoken language resources across the CLARIN infrastructure and beyond.
We present a method for detecting and reconstructing separated particle verbs in a corpus of spoken German by following an approach suggested for written language. Our study shows that the method can be applied successfully to spoken language, compares different ways of dealing with structures that are specific to spoken language corpora, analyses some remaining problems, and discusses ways of optimising precision or recall for the method. The outlook sketches some possibilities for further work in related areas.
In this paper, we address two problems in indexing and querying spoken language corpora with overlapping speaker contributions. First, we look into how token distance and token precedence can be measured when multiple primary data streams are available and when transcriptions happen to be tokenized, but are not synchronized with the sound at the level of individual tokens. We propose and experiment with a speaker based search mode that enables any speaker’s transcription tier to be the basic tokenization layer whereby the contributions of other speakers are mapped to this given tier. Secondly, we address two distinct methods of how speaker overlaps can be captured in the TEI based ISO Standard for Spoken Language Transcriptions (ISO 24624:2016) and how they can be queried by MTAS – an open source Lucene-based search engine for querying text with multilevel annotations. We illustrate the problems, introduce possible solutions and discuss their benefits and drawbacks.