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Dear colleague,

We are happy to announce an additional webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). Instead of the usual afternoon hour, it will take place at 10:00am CET (June 24).

Next webinar:

Speaker: Mikel Artetxe (FAIR (Meta AI))     Title: Is scale all you need?     Date: Jun 24, 2022, 10:00 CET     Summary: The development of advanced spoken language technologies based on automatic speech recognition (ASR) and text-to-speech synthesis (TTS) has enabled computers to either learn how to listen or speak. Many applications and services are now available but still support fewer than 100 languages. Nearly 7000 living languages that are spoken by 350 million people remain uncovered. This is because the construction is commonly done based on machine learning trained in a supervised fashion where a large amount of paired speech and corresponding transcription is required. In this talk, we will introduce a semi-supervised learning mechanism based on a machine speech chain framework. First, we describe the primary machine speech chain architecture that learns not only to listen or speak but also to listen while speaking. The framework enables ASR and TTS to teach each other given unpaired data. After that, we describe the use of machine speech chain for code-switching and cross-lingual ASR and TTS of several languages, including low-resourced ethnic languages. Finally, we describe the recent multimodal machine chain that mimics overall human communication to listen while speaking and visualizing. With the support of image captioning and production models, the framework enables ASR and TTS to improve their performance using an image-only dataset.     Summary: Every once in a while, a new language model with gazillion parameters makes a big splash in Twitter, smashing the previous SOTA in some benchmarks or showing some impressive emerging capabilities. While some may argue that scaling will eventually solve NLP, others are skeptical about the scientific value of this trend. In this talk, I will argue that scaling is not just engineering, but also comes with exciting research questions. I will present some of our recent work in the topic, and discuss our efforts to make large language models more accessible for the community.     Bio:Mikel Artetxe is a Research Scientist at FAIR (Meta AI). His primary area of research is multilingual NLP. Mikel was one the pioneers of unsupervised machine translation, and has done extensive work on cross-lingual representation learning. More recently, he has also been working on natural language generation, few-shot learning, and large-scale language models. Prior to joining FAIR, Mikel did his PhD at the IXA group at the University of the Basque Country, and interned at DeepMind, FAIR and Google.

Check past and upcoming webinars at the following url: http://www.hitz.eus/webinars If you are interested in participating, please complete this registration form: http://www.hitz.eus/webinar_izenematea

If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info

Best wishes,

HiTZ Zentroa

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