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Found 5 papers, 0 papers with code
Multimodal Contextual Dialogue Breakdown Detection for Conversational AI Models
Detecting dialogue breakdown in real time is critical for conversational AI systems, because it enables taking corrective action to successfully complete a task.
Graph Integrated Language Transformers for Next Action Prediction in Complex Phone Calls
Current Conversational AI systems employ different machine learning pipelines, as well as external knowledge sources and business logic to predict the next action.
Leveraging Explicit Procedural Instructions for Data-Efficient Action Prediction
Task-oriented dialogues often require agents to enact complex, multi-step procedures in order to meet user requests.
Entity resolution for noisy ASR transcripts
Large vocabulary domain-agnostic Automatic Speech Recognition (ASR) systems often mistranscribe domain-specific words and phrases.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Developing Production-Level Conversational Interfaces with Shallow Semantic Parsing
We demonstrate an end-to-end approach for building conversational interfaces from prototype to production that has proven to work well for a number of applications across diverse verticals.
