127 - Masakhane and Participatory Research for African Languages, with Tosin Adewumi and Perez Ogayo

127 - Masakhane and Participatory Research for African Languages, with Tosin Adewumi and Perez Ogayo

Author: Allen Institute for Artificial Intelligence June 9, 2021 Duration: 47:17
We invited members of Masakhane, Tosin Adewumi and Perez Ogayo, to talk about their EMNLP Findings paper that discusses why typical research is limited for low-resourced NLP and how participatory research can help.   As a result of participatory research, Masakhane has many, many success stories: first datasets and benchmarks in African languages, first research on human evaluation specifically for MT for low-resource languages, etc. In this episode, we talked about one of them—MasakhaNER—in more detail. The hosts for this episode are Pradeep Dasigi and Ana Marasović. -------------------------- Tosin Adewumi is a PhD student at the Luleå University of Technology in Sweden. His Twitter handle: @tosintwit Perez Ogayo is an undergrad student at the African Leadership University in Rwanda. Her Twitter handle: @a_ogayo Masakhane is a grassroots organization whose mission is to strengthen and spur NLP research in African languages, for Africans, by Africans: https://www.masakhane.io/ Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages (Findings of EMNLP 2020): https://arxiv.org/abs/2010.02353 MasakhaNER: Named Entity Recognition for African languages (AfricaNLP Workshop @ EACL 2021): https://arxiv.org/abs/2103.11811

While NLP Highlights is currently on hiatus, its archive remains a compelling snapshot of conversations from the front lines of computational linguistics. Produced by the Allen Institute for Artificial Intelligence, this science podcast carved out a space for deep, researcher-led discussions about natural language processing. Each episode functions as an informal seminar, where the people actively designing algorithms and pushing the field forward explain their work in their own words. You'll hear about the nuanced challenges behind making machines understand, generate, and reason with human language, from foundational theories to unexpected applications. The dialogue in this podcast often delves into the "why" behind the research, not just the results, offering clarity on complex topics like machine translation, sentiment analysis, or large language models. It’s a chance to listen as experts articulate their thought processes, debates, and moments of insight, with all the candidness that comes from a conversation between peers. The views shared are personal perspectives from the hosts and their guests, independent of their affiliated institutions. For anyone curious about how machines learn to parse meaning, the archived episodes of NLP Highlights provide a thoughtful and accessible entry point.
Author: Language: English Episodes: 50

NLP Highlights
Podcast Episodes
123 - Robust NLP, with Robin Jia [not-audio_url] [/not-audio_url]

Duration: 47:59
In this episode, Robin Jia talks about how to build robust NLP systems. We discuss the different senses in which a system can be robust, reasons to care about system robustness, and the challenges involved in evaluating…
122 - Statutory Reasoning in Tax Law, with Nils Holzenberger [not-audio_url] [/not-audio_url]

Duration: 46:18
We invited Nils Holzenberger, a PhD student at JHU to talk about a dataset involving statutory reasoning in tax law Holzenberger et al. released recently. This dataset includes difficult textual entailment and question a…
121 - Language and the Brain, with Alona Fyshe [not-audio_url] [/not-audio_url]

Duration: 42:38
We invited Alona Fyshe to talk about the link between NLP and the human brain. We began by talking about what we currently know about the connection between representations used in NLP and representations recorded in the…
120 - Evaluation of Text Generation, with Asli Celikyilmaz [not-audio_url] [/not-audio_url]

Duration: 55:13
We invited Asli Celikyilmaz for this episode to talk about evaluation of text generation systems. We discussed the challenges in evaluating generated text, and covered human and automated metrics, with a discussion of re…
119 - Social NLP, with Diyi Yang [not-audio_url] [/not-audio_url]

Duration: 53:32
In this episode, Diyi Yang gives us an overview of using NLP models for social applications, including understanding social relationships, processes, roles, and power. As NLP systems are getting used more and more in the…
118 - Coreference Resolution, with Marta Recasens [not-audio_url] [/not-audio_url]

Duration: 47:30
In this episode, we talked about Coreference Resolution with Marta Recasens, a Research Scientist at Google. We discussed the complexity involved in resolving references in language, the simplification of the problem tha…
117 - Interpreting NLP Model Predictions, with Sameer Singh [not-audio_url] [/not-audio_url]

Duration: 56:56
We interviewed Sameer Singh for this episode, and discussed an overview of recent work in interpreting NLP model predictions, particularly instance-level interpretations. We started out by talking about why it is importa…
116 - Grounded Language Understanding, with Yonatan Bisk [not-audio_url] [/not-audio_url]

Duration: 59:28
We invited Yonatan Bisk to talk about grounded language understanding. We started off by discussing an overview of the topic, its research goals, and the the challenges involved. In the latter half of the conversation, w…
115 - AllenNLP, interviewing Matt Gardner [not-audio_url] [/not-audio_url]

Duration: 33:25
In this special episode, Carissa Schoenick, a program manager and communications director at AI2 interviewed Matt Gardner about AllenNLP. We chatted about the origins of AllenNLP, the early challenges in building it, and…
114 - Behavioral Testing of NLP Models, with Marco Tulio Ribeiro [not-audio_url] [/not-audio_url]

Duration: 43:32
We invited Marco Tulio Ribeiro, a Senior Researcher at Microsoft, to talk about evaluating NLP models using behavioral testing, a framework borrowed from Software Engineering. Marco describes three kinds of black-box tes…