On the Importance of Signer Overlap for Sign Language Detection

no code implementations • 19 Mar 2023 • Abhilash Pal, Stephan Huber, Cyrine Chaabani, Alessandro Manzotti, Oscar Koller

We quantify this with a detailed analysis of the effect of signer overlap on current sign detection benchmark data sets.

Sign Language Recognition

Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems

no code implementations • 15 Jun 2022 • Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudre, Dilek Hakkani-Tur, Wael Hamza, Jonathan Hueser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Liz Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gokhan Tur, Prem Natarajan

We present results from a large-scale experiment on pretraining encoders with non-embedding parameter counts ranging from 700M to 9. 3B, their subsequent distillation into smaller models ranging from 17M-170M parameters, and their application to the Natural Language Understanding (NLU) component of a virtual assistant system.

Cross-Lingual Natural Language Inference intent-classification +5

Semantic Diversity for Natural Language Understanding Evaluation in Dialog Systems

no code implementations • COLING 2020 • Enrico Palumbo, Andrea Mezzalira, Cristina Marco, Alessandro Manzotti, Daniele Amberti

In this paper, we introduce the task of generating a test set with high semantic diversity for NLU evaluation in dialog systems and we describe an approach to address it.

Clustering Natural Language Understanding