87 citations · 218 across the 10 of their papers we have counts for
11 papers
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon AGI, Aaron Langford, Aayush Shah +783
We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…
Alexa, play with robot: Introducing the First Alexa Prize SimBot Challenge on Embodied AI
Hangjie Shi, Leslie Ball, Govind Thattai +39
The Alexa Prize program has empowered numerous university students to explore, experiment, and showcase their talents in building conversational agents through challenges like the…
Alexa Arena: A User-Centric Interactive Platform for Embodied AI
Qiaozi Gao, Govind Thattai, Suhaila Shakiah +24
We introduce Alexa Arena, a user-centric simulation platform for Embodied AI (EAI) research. Alexa Arena provides a variety of multi-room layouts and interactable objects, for the…
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…
Flexible and Scalable State Tracking Framework for Goal-Oriented Dialogue Systems
Rahul Goel, Shachi Paul, Tagyoung Chung +3
Goal-oriented dialogue systems typically rely on components specifically developed for a single task or domain. This limits such systems in two different ways: If there is an updat…
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…