no code implementations • 7 Aug 2023 • Cecilia Aas, Hisham Abdelsalam, Irina Belousova, Shruti Bhargava, Jianpeng Cheng, Robert Daland, Joris Driesen, Federico Flego, Tristan Guigue, Anders Johannsen, Partha Lal, Jiarui Lu, Joel Ruben Antony Moniz, Nathan Perkins, Dhivya Piraviperumal, Stephen Pulman, Diarmuid Ó Séaghdha, David Q. Sun, John Torr, Marco Del Vecchio, Jay Wacker, Jason D. Williams, Hong Yu
It has recently become feasible to run personal digital assistants on phones and other personal devices.
no code implementations • 17 Mar 2023 • Zidi Xiu, Kai-Chen Cheng, David Q. Sun, Jiannan Lu, Hadas Kotek, Yuhan Zhang, Paul McCarthy, Christopher Klein, Stephen Pulman, Jason D. Williams
Next, we expand the time horizon to examine behavior changes and show that as users discover the limitations of the IA's understanding and functional capabilities, they learn to adjust the scope and wording of their requests to increase the likelihood of receiving a helpful response from the IA.
no code implementations • EMNLP (NLP4ConvAI) 2021 • Sahas Dendukuri, Pooja Chitkara, Joel Ruben Antony Moniz, Xiao Yang, Manos Tsagkias, Stephen Pulman
Entity tags in human-machine dialog are integral to natural language understanding (NLU) tasks in conversational assistants.
no code implementations • 15 Aug 2021 • Deepak Muralidharan, Joel Ruben Antony Moniz, Weicheng Zhang, Stephen Pulman, Lin Li, Megan Barnes, Jingjing Pan, Jason Williams, Alex Acero
Named entity recognition (NER) is usually developed and tested on text from well-written sources.
2 code implementations • NAACL 2021 • Raviteja Anantha, Svitlana Vakulenko, Zhucheng Tu, Shayne Longpre, Stephen Pulman, Srinivas Chappidi
We introduce a new dataset for Question Rewriting in Conversational Context (QReCC), which contains 14K conversations with 80K question-answer pairs.
no code implementations • NAACL 2021 • Deepak Muralidharan, Joel Ruben Antony Moniz, Sida Gao, Xiao Yang, Justine Kao, Stephen Pulman, Atish Kothari, Ray Shen, Yinying Pan, Vivek Kaul, Mubarak Seyed Ibrahim, Gang Xiang, Nan Dun, Yidan Zhou, Andy O, Yuan Zhang, Pooja Chitkara, Xuan Wang, Alkesh Patel, Kushal Tayal, Roger Zheng, Peter Grasch, Jason D. Williams, Lin Li
Named Entity Recognition (NER) and Entity Linking (EL) play an essential role in voice assistant interaction, but are challenging due to the special difficulties associated with spoken user queries.
no code implementations • 4 May 2020 • Raviteja Anantha, Stephen Pulman, Srinivas Chappidi
We present a generic and flexible Reinforcement Learning (RL) based meta-learning framework for the problem of few-shot learning.
no code implementations • 25 Jan 2020 • Pranay Dighe, Saurabh Adya, Nuoyu Li, Srikanth Vishnubhotla, Devang Naik, Adithya Sagar, Ying Ma, Stephen Pulman, Jason Williams
A pure trigger-phrase detector model doesn't fully utilize the intent of the user speech whereas by using the complete decoding lattice of user audio, we can effectively mitigate speech not intended for the smart assistant.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • 18 Sep 2019 • Deepak Muralidharan, Justine Kao, Xiao Yang, Lin Li, Lavanya Viswanathan, Mubarak Seyed Ibrahim, Kevin Luikens, Stephen Pulman, Ashish Garg, Atish Kothari, Jason Williams
Personal assistant AI systems such as Siri, Cortana, and Alexa have become widely used as a means to accomplish tasks through natural language commands.
no code implementations • 29 Aug 2019 • Xi C. Chen, Adithya Sagar, Justine T. Kao, Tony Y. Li, Christopher Klein, Stephen Pulman, Ashish Garg, Jason D. Williams
We describe a method for selecting relevant new training data for the LSTM-based domain selection component of our personal assistant system.
2 code implementations • 4 Dec 2014 • Lei Yu, Karl Moritz Hermann, Phil Blunsom, Stephen Pulman
Answer sentence selection is the task of identifying sentences that contain the answer to a given question.
Ranked #3 on Question Answering on QASent
no code implementations • 23 Jan 2014 • Dimitri Kartsaklis, Mehrnoosh Sadrzadeh, Stephen Pulman, Bob Coecke
They also provide semantics for Lambek's pregroup algebras, applied to formalizing the grammatical structure of natural language, and are implicit in a distributional model of word meaning based on vector spaces.
no code implementations • 2 May 2013 • Stephen Clark, Bob Coecke, Edward Grefenstette, Stephen Pulman, Mehrnoosh Sadrzadeh
We discuss an algorithm which produces the meaning of a sentence given meanings of its words, and its resemblance to quantum teleportation.