Augmented datasheets for speech datasets and ethical decision-making
Speech datasets are crucial for training Speech Language Technologies (SLT); however,
the lack of diversity of the underlying training data can lead to serious limitations in building …
the lack of diversity of the underlying training data can lead to serious limitations in building …
Out-of-distribution generalization in natural language processing: Past, present, and future
Abstract Machine learning (ML) systems in natural language processing (NLP) face
significant challenges in generalizing to out-of-distribution (OOD) data, where the test …
significant challenges in generalizing to out-of-distribution (OOD) data, where the test …
Hi guys or hi folks? benchmarking gender-neutral machine translation with the gente corpus
Gender inequality is embedded in our communication practices and perpetuated in
translation technologies. This becomes particularly apparent when translating into …
translation technologies. This becomes particularly apparent when translating into …
Contrastive conditioning for assessing disambiguation in MT: A case study of distilled bias
Lexical disambiguation is a major challenge for machine translation systems, especially if
some senses of a word are trained less often than others. Identifying patterns of …
some senses of a word are trained less often than others. Identifying patterns of …
Test suites task: Evaluation of gender fairness in MT with MuST-SHE and INES
As part of the WMT-2023" Test suites" shared task, in this paper we summarize the results of
two test suites evaluations: MuST-SHE-WMT23 and INES. By focusing on the en-de and de …
two test suites evaluations: MuST-SHE-WMT23 and INES. By focusing on the en-de and de …
A prompt response to the demand for automatic gender-neutral translation
Gender-neutral translation (GNT) that avoids biased and undue binary assumptions is a
pivotal challenge for the creation of more inclusive translation technologies. Advancements …
pivotal challenge for the creation of more inclusive translation technologies. Advancements …
Out-of-distribution generalization in text classification: Past, present, and future
Machine learning (ML) systems in natural language processing (NLP) face significant
challenges in generalizing to out-of-distribution (OOD) data, where the test distribution …
challenges in generalizing to out-of-distribution (OOD) data, where the test distribution …
Demystifying ChatGPT: An In-depth Survey of OpenAI's Robust Large Language Models
Recent advancements in natural language processing (NLP) have catalyzed the
development of models capable of generating coherent and contextually relevant …
development of models capable of generating coherent and contextually relevant …
Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection from English Speech Signals
Speech emotion recognition (SER) plays a vital role in various applications, enabling
machines to decode and analyze emotions conveyed through speech. This study introduces …
machines to decode and analyze emotions conveyed through speech. This study introduces …
Indigenous language revitalization and the dilemma of gender bias
Abstract Natural Language Processing (NLP), through its several applications, has been
considered as one of the most valuable field in interdisciplinary researches, as well as in …
considered as one of the most valuable field in interdisciplinary researches, as well as in …