This paper introduces FT Speech, a new speech corpus created from the recorded meetings of the Danish Parliament, otherwise known as the Folketing (FT). The corpus contains over 1,800 hours of transcribed speech by a total of 434 speakers. It is significantly larger in duration, vocabulary, and amount of spontaneous speech than the existing public speech corpora for Danish, which are largely limited to read-aloud and dictation data. We outline design considerations, including the preprocessing methods and the alignment procedure. To evaluate the quality of the corpus, we train automatic speech recognition systems on the new resource and compare them to the systems trained on the Danish part of Språkbanken, the largest public ASR corpus for Danish to date. Our baseline results show that we achieve a 14.01 WER on the new corpus. A combination of FT Speech with in-domain language data provides comparable results to models trained specifically on Språkbanken, showing that FT Speech transfers well to this data set. Interestingly, our results demonstrate that the opposite is not the case. This shows that FT Speech provides a valuable resource for promoting research on Danish ASR with more spontaneous speech.
Institute for Data Science（数据科学研究所）；University of Applied Sciences and Arts Northwestern Switzerland（瑞士西北应用科学与艺术大学）
We present the Swiss Parliaments Corpus (SPC), an automatically aligned Swiss German speech to Standard German text corpus. This first version of the corpus is based on publicly available data of the Bernese cantonal parliament and consists of 293 hours of data. It was created using a novel forced sentence alignment procedure and an alignment quality estimator, which can be used to trade off corpus size and quality. We trained Automatic Speech Recognition (ASR) models as baselines on different subsets of the data and achieved a Word Error Rate (WER) of 0.278 and a BLEU score of 0.586 on the SP…
Public sources like parliament meeting recordings and transcripts provide ever-growing material for the training and evaluation of automatic speech recognition (ASR) systems. In this paper, we publish and analyse the Finnish parliament ASR corpus, the largest publicly available collection of manually transcribed speech data for Finnish with over 3000 hours of speech and 449 speakers for which it provides rich demographic metadata. This corpus builds on earlier initial work, and as a result the corpus has a natural split into two training subsets from two periods of time. Similarly, there are t…
National Library of Norway（挪威国家图书馆）；Telenor Research（Telenor研究院）
The Norwegian Parliamentary Speech Corpus (NPSC) is a speech dataset with recordings of meetings from Stortinget, the Norwegian parliament. It is the first, publicly available dataset containing unscripted, Norwegian speech designed for training of automatic speech recognition (ASR) systems. The recordings are manually transcribed and annotated with language codes and speakers, and there are detailed metadata about the speakers. The transcriptions exist in both normalized and non-normalized form, and non-standardized words are explicitly marked and annotated with standardized equivalents. To t…
Valencian Research Institute for Artificial Intelligence (VRAIN)（巴伦西亚人工智能研究所（VRAIN））
Current research into spoken language translation (SLT),or speech-to-text translation, is often hampered by the lack of specific data resources for this task, as currently available SLT datasets are restricted to a limited set of language pairs. In this paper we present Europarl-ST, a novel multilingual SLT corpus containing paired audio-text samples for SLT from and into 6 European languages, for a total of 30 different translation directions. This corpus has been compiled using the debates held in the European Parliament in the period between 2008 and 2012. This paper describes the corpus cr…
University of Copenhagen（哥本哈根大学）；IT University of Copenhagen（哥本哈根信息技术大学）
Eye movement recordings from reading are one of the richest signals of human language processing. Corpora of eye movements during reading of contextualized running text is a way of making such records available for natural language processing purposes. Such corpora already exist in some languages. We present CopCo, the Copenhagen Corpus of eye tracking recordings from natural reading of Danish texts. It is the first eye tracking corpus of its kind for the Danish language. CopCo includes 1,832 sentences with 34,897 tokens of Danish text extracted from a collection of speech manuscripts. This fi…
Instituto Gulbenkian de Ciência（古尔本基安科学研究所）；Nova School of Business and Economics, Universidade Nova de Lisboa（新里斯本大学新商业与经济学院）；CICANT, Universidade Lusófona (ULHT)（卢索福纳大学（ULHT）传播与应用语言学研究中心）
In a representative democracy, some decide in the name of the rest, and these elected officials are commonly gathered in public assemblies, such as parliaments, where they discuss policies, legislate, and vote on fundamental initiatives. A core aspect of such democratic processes are the plenary debates, where important public discussions take place. Many parliaments around the world are increasingly keeping the transcripts of such debates, and other parliamentary data, in digital formats accessible to the public, increasing transparency and accountability. Furthermore, some parliaments are br…
ITU Copenhagen（哥本哈根信息技术大学）；USC Information Sciences Institute（南加州大学信息科学研究所）；Aarhus University（奥胡斯大学）；Cornell University（康奈尔大学）；Danish Language Council（丹麦语言委员会）；Alexandra Institute（亚历山德拉研究所）；University of Copenhagen（哥本哈根大学）；TV2 Regionerne（TV2区域台）；Technical University of Denmark（丹麦技术大学）；Karnov Group（卡诺夫集团）；Novo Nordisk（诺和诺德）
Danish language technology has been hindered by a lack of broad-coverage corpora at the scale modern NLP prefers. This paper describes the Danish Gigaword Corpus, the result of a focused effort to provide a diverse and freely-available one billion word corpus of Danish text. The Danish Gigaword corpus covers a wide array of time periods, domains, speakers' socio-economic status, and Danish dialects.
HiTZ Center - Ixa, University of the Basque Country UPV/EHU（巴斯克大学UPV/EHU HiTZ中心-Ixa）；Gureiker, University of the Basque Country UPV/EHU（巴斯克大学UPV/EHU Gureiker）
Parliamentary transcripts provide a valuable resource to understand the reality and know about the most important facts that occur over time in our societies. Furthermore, the political debates captured in these transcripts facilitate research on political discourse from a computational social science perspective. In this paper we release the first version of a newly compiled corpus from Basque parliamentary transcripts. The corpus is characterized by heavy Basque-Spanish code-switching, and represents an interesting resource to study political discourse in contrasting languages such as Basque…
EmoTale: An Enacted Speech-emotion Dataset in Danish
University Grenoble Alpes, CNRS, Grenoble INP, LIG（格陵兰大学、CNRS、格陵兰INP、LIG）；Dept. of Applied Mathematics and Computer Science, Technical University of Denmark（应用数学和计算机科学系，丹麦技术大学）
National Technical University of Athens（雅典国家技术大学）；Institute for Speech and Language Processing, Athena Research Center（雅典娜研究中心语音与语言处理研究所）
Modern speech recognition systems exhibits rapid performance degradation under domain shift. This issue is especially prevalent in data-scarce settings, such as low-resource languages, where diversity of training data is limited. In this work we propose M2DS2, a simple and sample-efficient finetuning strategy for large pretrained speech models, based on mixed source and target domain self-supervision. We find that including source domain self-supervision stabilizes training and avoids mode collapse of the latent representations. For evaluation, we collect HParl, a $120$ hour speech corpus for …
Opinionated, Hesitant and Stressed: Three Studies of How Politicians Speak in Four Slavic Parliaments
Jožef Stefan Institute（约热夫·斯泰凡研究所）；Institute of Contemporary History（当代历史研究所）；Faculty of Computer and Information Science, University of Ljubljana（卢布尔雅那大学计算机与信息科学学院）
Meta AI Research（Meta人工智能研究院）；Inria（法国国家信息与自动化研究所）
We present SpeechMatrix, a large-scale multilingual corpus of speech-to-speech translations mined from real speech of European Parliament recordings. It contains speech alignments in 136 language pairs with a total of 418 thousand hours of speech. To evaluate the quality of this parallel speech, we train bilingual speech-to-speech translation models on mined data only and establish extensive baseline results on EuroParl-ST, VoxPopuli and FLEURS test sets. Enabled by the multilinguality of SpeechMatrix, we also explore multilingual speech-to-speech translation, a topic which was addressed by fe…
West Greenlandic, known by native speakers as Kalaallisut, is an extremely low-resource polysynthetic language spoken by around 56,000 people in Greenland. Here, we attempt to finetune a pretrained Kalaallisut-to-English neural machine translation (NMT) system using web-crawled pseudoparallel sentences from around 30 multilingual websites. We compile a corpus of over 93,000 Kalaallisut sentences and over 140,000 Danish sentences, then use cross-lingual sentence embeddings and approximate nearest-neighbors search in an attempt to mine near-translations from these corpora. Finally, we translate …
Does Whisper understand Swiss German? An automatic, qualitative, and human evaluation
Linguistics Center Zurich（苏黎世语言学中心）；German Department（德语系）；University of Zurich（苏黎世大学）；Department of Computational Linguistics（计算语言学系）；Phonetics & Speech Sciences（语音与言语科学系）
本文通过自动指标、定性分析和28人人工调查，在四个测试集上评估 Whisper 对瑞士德语的转写表现，证明其可作为输出标准德语的可行 ASR 系统。
School of Computer Science, The University of Manchester（曼彻斯特大学计算机科学学院）
This paper presents our investigations on emotional state categorization from speech signals with a psychologically inspired computational model against human performance under the same experimental setup. Based on psychological studies, we propose a multistage categorization strategy which allows establishing an automatic categorization model flexibly for a given emotional speech categorization task. We apply the strategy to the Serbian Emotional Speech Corpus (GEES) and the Danish Emotional Speech Corpus (DES), where human performance was reported in previous psychological studies. Our work …
This paper describes an interdisciplinary approach which brings together the fields of corpus linguistics and translation studies. It presents ongoing work on the creation of a corpus resource in which translation shifts are explicitly annotated. Translation shifts denote departures from formal correspondence between source and target text, i.e. deviations that have occurred during the translation process. A resource in which such shifts are annotated in a systematic way will make it possible to study those phenomena that need to be addressed if machine translation output is to resemble human …
DIETA: A Decoder-only transformer-based model for Italian-English machine TrAnslation
Department of Informatics, Systems and Communication - DISCo, University of Milano-Bicocca, Italy（信息与通信系统系 - DISCo，米兰-比科卡大学）；NVIDIA AI Technology Center, Italy（NVIDIA人工智能技术中心）
Parallel texts are a relatively rare language resource, however, they constitute a very useful research material with a wide range of applications. This study presents and analyses new methodologies we developed for obtaining such data from previously built comparable corpora. The methodologies are automatic and unsupervised which makes them good for large scale research. The task is highly practical as non-parallel multilingual data occur much more frequently than parallel corpora and accessing them is easy, although parallel sentences are a considerably more useful resource. In this study, w…
