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Found 11 papers, 6 papers with code
Facebook AI’s WMT20 News Translation Task Submission
We approach the low resource problem using two main strategies, leveraging all available data and adapting the system to the target news domain.
Audiobox: Unified Audio Generation with Natural Language Prompts
Research communities have made great progress over the past year advancing the performance of large scale audio generative models for a single modality (speech, sound, or music) through adopting more powerful generative models and scaling data.
Ranked #1 on
Audio Generation
on AudioCaps
A Picture is Worth More Than 77 Text Tokens: Evaluating CLIP-Style Models on Dense Captions
Curation methods for massive vision-language datasets trade off between dataset size and quality.
Seamless: Multilingual Expressive and Streaming Speech Translation
In this work, we introduce a family of models that enable end-to-end expressive and multilingual translations in a streaming fashion.
droidlet: modular, heterogenous, multi-modal agents
In recent years, there have been significant advances in building end-to-end Machine Learning (ML) systems that learn at scale.
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation
We introduce VoxPopuli, a large-scale multilingual corpus providing 100K hours of unlabelled speech data in 23 languages.
Ranked #3 on
Speech Recognition
on Common Voice French
(using extra training data)
I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling
To quantify how well natural language understanding models can capture consistency in a general conversation, we introduce the DialoguE COntradiction DEtection task (DECODE) and a new conversational dataset containing both human-human and human-bot contradictory dialogues.
Facebook AI's WMT20 News Translation Task Submission
We approach the low resource problem using two main strategies, leveraging all available data and adapting the system to the target news domain.
Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions
We present our view of what is necessary to build an engaging open-domain conversational agent: covering the qualities of such an agent, the pieces of the puzzle that have been built so far, and the gaping holes we have not filled yet.
Recipes for building an open-domain chatbot
Building open-domain chatbots is a challenging area for machine learning research.
Can You Put it All Together: Evaluating Conversational Agents' Ability to Blend Skills
Being engaging, knowledgeable, and empathetic are all desirable general qualities in a conversational agent.
