Abstract Over the past three decades, the fields of automatic speech recognition (ASR) and machine translation (MT) have witnessed remarkable advancements, leading to exciting research directions such as speech-to-text translation (ST). This talk will delve[…]
Abstract There is an enormous data gap between how AI systems and children learn language: The best LLMs now learn language from text with a word count in the trillions, whereas it would take a[…]
Abstract Large language models like ChatGPT have shown extraordinary abilities for writing. While impressive at first glance, large language models aren’t perfect and often make mistakes humans would not make. The main architecture behind ChatGPT[…]
Abstract Our research focuses on improving speech processing algorithms, such as automatic speech recognition (ASR), speaker identification, and depression detection, under challenging conditions such as limited data (for example, children’s or clinical speech), mismatched conditions[…]
Abstract Non-invasive neural interfaces have the potential to transform human-computer interaction by providing users with low friction, information rich, always available inputs. Reality Labs at Meta is developing such an interface for the control of[…]
Abstract Foundation models, including Chat-GPT and its many variants, have come into prominence in the natural language processing (NLP) community thanks the ubiquity of text data readily available on the internet and the design of[…]
Abstract Pre-trained speech representation models have become ubiquitous in speech processing over the past few years. They have both improved the state of the art and made it feasible to learn task-specific models with very[…]
Abstract The almost unlimited multimedia content available on video-sharing websites has opened new challenges and opportunities for building robust multimodal solutions. This seminar will describe our novel multimodal architectures that (1) are robust to missing[…]
