Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Speech (2)
- Annotation (1)
- Artificial intelligence (1)
- Computer science education (1)
- Corpus (1)
-
- Crowdsourcing (1)
- Discrimination (1)
- Emotional speech (1)
- Ethics washing (1)
- Gender computing (1)
- Gender diversity in cs (1)
- Healthcare discrimination (1)
- Judgement analysis (1)
- Labelling (1)
- Low-pass filtered (1)
- MIPs (1)
- Mood Induced Speech (1)
- Mood Induction Procedure (1)
- Mood induced procedures (1)
- Natural Emotional Speech (1)
- Naturalistic emotional speech corpora (1)
- Online rating tool (1)
- Queer people (1)
- Socio technical systems (1)
- Speech assets (1)
- Web-tool (1)
- Women in computer science (1)
Articles 1 - 5 of 5
Full-Text Articles in Computer Engineering
Queer In Ai: A Case Study In Community-Led Participatory Ai, Anaelia Ovalle, Arjun Subramonian, Ashwiin Singh, Claas Voelcker, Danica Sutherland, Davide Locatelli, Eva Breznik, Felip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Melind Agarwal, Nyx Mclean, Pan Xu, A. Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, S.T. John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark
Queer In Ai: A Case Study In Community-Led Participatory Ai, Anaelia Ovalle, Arjun Subramonian, Ashwiin Singh, Claas Voelcker, Danica Sutherland, Davide Locatelli, Eva Breznik, Felip Klubicka, Hang Yuan, Hetvi J, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Melind Agarwal, Nyx Mclean, Pan Xu, A. Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, S.T. John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew Mcnamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark
Conference papers
Queerness and queer people face an uncertain future in the face of ever more widely deployed and invasive artificial intelligence (AI). These technologies have caused numerous harms to queer people, including privacy violations, censoring and downranking queer content, exposing queer people and spaces to harassment by making them hypervisible, deadnaming and outing queer people. More broadly, they have violated core tenets of queerness by classifying and controlling queer identities. In response to this, the queer community in AI has organized Queer in AI, a global, decentralized, volunteer-run grassroots organization that employs intersectional and community-led participatory design to build an inclusive …
Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education, Alina Berry, Susan Mckeever, Brenda Murphy, Sarah Jane Delany
Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education, Alina Berry, Susan Mckeever, Brenda Murphy, Sarah Jane Delany
Conference papers
Gender imbalance in computing education is a well-known issue around the world. For example, in the UK and Ireland, less than 20% of the student population in computer science, ICT and related disciplines are women. Similar figures are seen in the labour force in the field across the EU. The term "leaky pipeline"; is often used to describe the lack of retention of women before they progress to senior roles. Numerous initiatives have targeted the problem of the leaky pipeline in recent decades. This paper provides a comprehensive review of initiatives related to techniques used to boost recruitment and improve …
A Crowdsourcing Approach To Labelling A Mood Induced Speech Corpus, John Snel, Alexey Tarasov, Charlie Cullen, Sarah Jane Delany
A Crowdsourcing Approach To Labelling A Mood Induced Speech Corpus, John Snel, Alexey Tarasov, Charlie Cullen, Sarah Jane Delany
Conference papers
This paper demonstrates the use of crowdsourcing to accumulate ratings from na ̈ıve listeners as a means to provide labels for a naturalistic emotional speech dataset. In order to do so, listening tasks are performed with a rating tool, which is delivered via the web. The rating requirements are based on the classical dimensions, activation and evaluation, presented to the participant as two discretised 5-point scales. Great emphasis is placed on the participant’s overall understanding of the task, and on the ease-of-use of the tool so that labelling accuracy is reinforced. The accumulation process is ongoing with a goal to …
Obtaining Speech Assets For Judgement Analysis On Low-Pass Filtered Emotional Speech, John Snel, Charlie Cullen
Obtaining Speech Assets For Judgement Analysis On Low-Pass Filtered Emotional Speech, John Snel, Charlie Cullen
Conference papers
Investigating the emotional content in speech from acoustic characteristics requires separating the semantic con- tent from the acoustic channel. For natural emotional speech, a widely used method to separate the two channels is the use of cue masking. Our objective is to investigate the use of cue masking in non-acted emotional speech by analyzing the extent to which filtering impacts the perception of emotional content of the modified speech material. However, obtaining a corpus of emotional speech can be quite difficult whereby verifying the emotional content is an issue thoroughly discussed. Currently, speech research is showing a tendency toward constructing …
Emotional Speech Corpus Construction, Annotation And Distribution, Brian Vaughan, Charlie Cullen, Spyros Kousidis, John Mcauley
Emotional Speech Corpus Construction, Annotation And Distribution, Brian Vaughan, Charlie Cullen, Spyros Kousidis, John Mcauley
Conference papers
This paper details a process of creating an emotional speech corpus by collecting natural emotional speech assets, analysisng and tagging them (for certain acoustic and linguistic features) and annotating them within an on-line database. The definition of specific metadata for use with an emotional speech corpus is crucial, in that poorly (or inaccurately) annotated assets are of little use in analysis. This problem is compounded by the lack of standardisation for speech corpora, particularly in relation to emotion content. The ISLE Metadata Initiative (IMDI) is the only cohesive attempt at corpus metadata standardisation performed thus far. Although not a comprehensive …