14 citations · 45 across the 8 of their papers we have counts for
5 papers · 1 filter
Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs
Abishek Komma, Nagesh Panyam Chandrasekarasastry, Timothy Leffel +4
Measurement of interaction quality is a critical task for the improvement of spoken dialog systems. Existing approaches to dialog quality estimation either focus on evaluating the…
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration
Han Li, Sunghyun Park, Aswarth Dara +5
Current state-of-the-art large-scale conversational AI or intelligent digital assistant systems in industry comprises a set of components such as Automatic Speech Recognition (ASR)…
Joint Turn and Dialogue level User Satisfaction Estimation on Multi-Domain Conversations
Praveen Kumar Bodigutla, Aditya Tiwari, Josep Valls Vargas +2
Dialogue level quality estimation is vital for optimizing data driven dialogue management. Current automated methods to estimate turn and dialogue level user satisfaction employ ha…
Data Augmentation for Training Dialog Models Robust to Speech Recognition Errors
Longshaokan Wang, Maryam Fazel-Zarandi, Aditya Tiwari +2
Speech-based virtual assistants, such as Amazon Alexa, Google assistant, and Apple Siri, typically convert users' audio signals to text data through automatic speech recognition (A…
Investigation of Error Simulation Techniques for Learning Dialog Policies for Conversational Error Recovery
Maryam Fazel-Zarandi, Longshaokan Wang, Aditya Tiwari +1
Training dialog policies for speech-based virtual assistants requires a plethora of conversational data. The data collection phase is often expensive and time consuming due to huma…