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Found 34 papers, 7 papers with code
ZHAW-InIT - Social Media Geolocation at VarDial 2020
We describe our approaches for the Social Media Geolocation (SMG) task at the VarDial Evaluation Campaign 2020.
Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets
Dialogue summarization is a long-standing task in the field of NLP, and several data sets with dialogues and associated human-written summaries of different styles exist.
Dialect Transfer for Swiss German Speech Translation
This paper investigates the challenges in building Swiss German speech translation systems, specifically focusing on the impact of dialect diversity and differences between Swiss German and Standard German.
Correction of Errors in Preference Ratings from Automated Metrics for Text Generation
A major challenge in the field of Text Generation is evaluation: Human evaluations are cost-intensive, and automated metrics often display considerable disagreement with human judgments.
STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions
We train an ASR model on the training set and achieve an average BLEU score of 74. 7 on the test set.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible.
On the Effectiveness of Automated Metrics for Text Generation Systems
A major challenge in the field of Text Generation is evaluation because we lack a sound theory that can be leveraged to extract guidelines for evaluation campaigns.
SDS-200: A Swiss German Speech to Standard German Text Corpus
We present SDS-200, a corpus of Swiss German dialectal speech with Standard German text translations, annotated with dialect, age, and gender information of the speakers.
Probing the Robustness of Trained Metrics for Conversational Dialogue Systems
This paper introduces an adversarial method to stress-test trained metrics to evaluate conversational dialogue systems.
Spot The Bot: A Robust and Efficient Framework for the Evaluation of Conversational Dialogue Systems
In this work, we introduce \emph{Spot The Bot}, a cost-efficient and robust evaluation framework that replaces human-bot conversations with conversations between bots.
DoQA - Accessing Domain-Specific FAQs via Conversational QA
We present DoQA, a dataset with 2, 437 dialogues and 10, 917 QA pairs.
DoQA -- Accessing Domain-Specific FAQs via Conversational QA
We present DoQA, a dataset with 2, 437 dialogues and 10, 917 QA pairs.
LEDGAR: A Large-Scale Multi-label Corpus for Text Classification of Legal Provisions in Contracts
We present LEDGAR, a multilabel corpus of legal provisions in contracts.
TRANSLIT: A Large-scale Name Transliteration Resource
Transliteration is the process of expressing a proper name from a source language in the characters of a target language (e. g. from Cyrillic to Latin characters).
CEASR: A Corpus for Evaluating Automatic Speech Recognition
In this paper, we present CEASR, a Corpus for Evaluating the quality of Automatic Speech Recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation
For this, we introduce an intermediate representation that is based on the logical query plan in a database called Operation Trees (OT).
Towards a Metric for Automated Conversational Dialogue System Evaluation and Improvement
We present "AutoJudge", an automated evaluation method for conversational dialogue systems.
Open-Ended Question Answering
Reinforcement Learning (RL)
+1
Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks
These words are used as a class description for more label-aware text classification.
Correlating Twitter Language with Community-Level Health Outcomes
We study how language on social media is linked to diseases such as atherosclerotic heart disease (AHD), diabetes and various types of cancer.
TwistBytes - Identification of Cuneiform Languages and German Dialects at VarDial 2019
The goal was to identify dialects of Swiss German in GDI and Sumerian and Akkadian in CLI.
Survey on Evaluation Methods for Dialogue Systems
We cover each class by introducing the main technologies developed for the dialogue systems and then by presenting the evaluation methods regarding this class.
Syntactic Manipulation for Generating more Diverse and Interesting Texts
In this work, we present our system for Natural Language Generation where we control various aspects of the surface realization in order to increase the lexical variability of the utterances, such that they sound more diverse and interesting.
Twist Bytes - German Dialect Identification with Data Mining Optimization
We describe our approaches used in the German Dialect Identification (GDI) task at the VarDial Evaluation Campaign 2018.
Transfer Learning and Sentence Level Features for Named Entity Recognition on Tweets
We present our system for the WNUT 2017 Named Entity Recognition challenge on Twitter data.
Ranked #22 on
Named Entity Recognition (NER)
on WNUT 2017
SwissAlps at SemEval-2017 Task 3: Attention-based Convolutional Neural Network for Community Question Answering
In this paper we propose a system for reranking answers for a given question.
TopicThunder at SemEval-2017 Task 4: Sentiment Classification Using a Convolutional Neural Network with Distant Supervision
In this paper, we propose a classifier for predicting topic-specific sentiments of English Twitter messages.
A Twitter Corpus and Benchmark Resources for German Sentiment Analysis
We use this new corpus and two existing corpora to provide state-of-the-art benchmarks for sentiment analysis in German: we implemented a CNN (based on the winning system of SemEval-2016) and a feature-based SVM and compare their performance on all three corpora.
Potential and Limitations of Cross-Domain Sentiment Classification
In this paper we investigate the cross-domain performance of a current state-of-the-art sentiment analysis systems.
Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification
This paper presents a novel approach for multi-lingual sentiment classification in short texts.
Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools
In this paper, we analyze the quality of several commercial tools for sentiment detection.
