87 citations · 218 across the 10 of their papers we have counts for
7 papers · 1 filter
Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems
Anish Acharya, Suranjit Adhikari, Sanchit Agarwal +28
Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Trai…
Advancing the State of the Art in Open Domain Dialog Systems through the Alexa Prize
Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh +19
Building open domain conversational systems that allow users to have engaging conversations on topics of their choice is a challenging task. Alexa Prize was launched in 2016 to tac…
Detecting Offensive Content in Open-domain Conversations using Two Stage Semi-supervision
Chandra Khatri, Behnam Hedayatnia, Rahul Goel +3
As open-ended human-chatbot interaction becomes commonplace, sensitive content detection gains importance. In this work, we propose a two stage semi-supervised approach to bootstra…
Parsing Coordination for Spoken Language Understanding
Sanchit Agarwal, Rahul Goel, Tagyoung Chung +3
Typical spoken language understanding systems provide narrow semantic parses using a domain-specific ontology. The parses contain intents and slots that are directly consumed by do…
Contextual Topic Modeling For Dialog Systems
Chandra Khatri, Rahul Goel, Behnam Hedayatnia +4
Accurate prediction of conversation topics can be a valuable signal for creating coherent and engaging dialog systems. In this work, we focus on context-aware topic classification…
Data Augmentation for Robust Keyword Spotting under Playback Interference
Anirudh Raju, Sankaran Panchapagesan, Xing Liu +2
Accurate on-device keyword spotting (KWS) with low false accept and false reject rate is crucial to customer experience for far-field voice control of conversational agents. It is…
Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting
Ming Sun, Anirudh Raju, George Tucker +6
We propose a max-pooling based loss function for training Long Short-Term Memory (LSTM) networks for small-footprint keyword spotting (KWS), with low CPU, memory, and latency requi…