Search Results for author: Judith Gaspers

Found 13 papers, 0 papers with code

Temporal Generalization for Spoken Language Understanding

no code implementations NAACL (ACL) 2022 Judith Gaspers, Anoop Kumar, Greg Ver Steeg, Aram Galstyan

Spoken Language Understanding (SLU) models in industry applications are usually trained offline on historic data, but have to perform well on incoming user requests after deployment.

Domain Generalization Spoken Language Understanding

The impact of domain-specific representations on BERT-based multi-domain spoken language understanding

no code implementations EACL (AdaptNLP) 2021 Judith Gaspers, Quynh Do, Tobias Röding, Melanie Bradford

This paper provides the first experimental study on the impact of using domain-specific representations on a BERT-based multi-task spoken language understanding (SLU) model for multi-domain applications.

Classification domain classification +6

To What Degree Can Language Borders Be Blurred In BERT-based Multilingual Spoken Language Understanding?

no code implementations COLING 2020 Quynh Do, Judith Gaspers, Tobias Roding, Melanie Bradford

This paper addresses the question as to what degree a BERT-based multilingual Spoken Language Understanding (SLU) model can transfer knowledge across languages.

Spoken Language Understanding

Data balancing for boosting performance of low-frequency classes in Spoken Language Understanding

no code implementations6 Aug 2020 Judith Gaspers, Quynh Do, Fabian Triefenbach

Despite the fact that data imbalance is becoming more and more common in real-world Spoken Language Understanding (SLU) applications, it has not been studied extensively in the literature.

intent-classification Intent Classification +4

Cross-lingual Transfer Learning with Data Selection for Large-Scale Spoken Language Understanding

no code implementations IJCNLP 2019 Quynh Do, Judith Gaspers

A typical cross-lingual transfer learning approach boosting model performance on a language is to pre-train the model on all available supervised data from another language.

Cross-Lingual Transfer Language Modelling +2

Cross-lingual transfer learning for spoken language understanding

no code implementations3 Apr 2019 Quynh Ngoc Thi Do, Judith Gaspers

Typically, spoken language understanding (SLU) models are trained on annotated data which are costly to gather.

Cross-Lingual Transfer Spoken Language Understanding +1

Neural Named Entity Recognition from Subword Units

no code implementations22 Aug 2018 Abdalghani Abujabal, Judith Gaspers

Named entity recognition (NER) is a vital task in spoken language understanding, which aims to identify mentions of named entities in text e. g., from transcribed speech.

named-entity-recognition Named Entity Recognition +2

Selecting Machine-Translated Data for Quick Bootstrapping of a Natural Language Understanding System

no code implementations NAACL 2018 Judith Gaspers, Penny Karanasou, Rajen Chatterjee

The goal is to decrease the cost and time needed to get an annotated corpus for the new language, while still having a large enough coverage of user requests.

Machine Translation Natural Language Understanding +1

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