Tomasz Ziętkiewicz

Also published as: Tomasz Zietkiewicz


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Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition Errors
Marek Kubis | Paweł Skórzewski | Marcin Sowański | Tomasz Zietkiewicz
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

In a spoken dialogue system, an NLU model is preceded by a speech recognition system that can deteriorate the performance of natural language understanding. This paper proposes a method for investigating the impact of speech recognition errors on the performance of natural language understanding models. The proposed method combines the back transcription procedure with a fine-grained technique for categorizing the errors that affect the performance of NLU models. The method relies on the usage of synthesized speech for NLU evaluation. We show that the use of synthesized speech in place of audio recording does not change the outcomes of the presented technique in a significant way.


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EUDAMU at SemEval-2017 Task 11: Action Ranking and Type Matching for End-User Development
Marek Kubis | Paweł Skórzewski | Tomasz Ziętkiewicz
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

The paper describes a system for end-user development using natural language. Our approach uses a ranking model to identify the actions to be executed followed by reference and parameter matching models to select parameter values that should be set for the given commands. We discuss the results of evaluation and possible improvements for future work.