5 citations · 8 across the 9 of their papers we have counts for
10 papers
Trustera: A Live Conversation Redaction System
Evandro Gouvêa, Ali Dadgar, Shahab Jalalvand +7
Trustera, the first functional system that redacts personally identifiable information (PII) in real-time spoken conversations to remove agents' need to hear sensitive information…
E2E Spoken Entity Extraction for Virtual Agents
Karan Singla, Yeon-Jun Kim, Srinivas Bangalore
In human-computer conversations, extracting entities such as names, street addresses and email addresses from speech is a challenging task. In this paper, we study the impact of fi…
Cross-stitched Multi-modal Encoders
Karan Singla, Daniel Pressel, Ryan Price +3
In this paper, we propose a novel architecture for multi-modal speech and text input. We combine pretrained speech and text encoders using multi-headed cross-modal attention and jo…
Seq-2-Seq based Refinement of ASR Output for Spoken Name Capture
Karan Singla, Shahab Jalalvand, Yeon-Jun Kim +3
Person name capture from human speech is a difficult task in human-machine conversations. In this paper, we propose a novel approach to capture the person names from the caller utt…
Unsupervised Spoken Utterance Classification
Shahab Jalalvand, Srinivas Bangalore
An intelligent virtual assistant (IVA) enables effortless conversations in call routing through spoken utterance classification (SUC) which is a special form of spoken language und…
Intent Features for Rich Natural Language Understanding
Brian Lester, Sagnik Ray Choudhury, Rashmi Prasad +1
Complex natural language understanding modules in dialog systems have a richer understanding of user utterances, and thus are critical in providing a better user experience. Howeve…
Constrained Decoding for Computationally Efficient Named Entity Recognition Taggers
Brian Lester, Daniel Pressel, Amy Hemmeter +2
Current state-of-the-art models for named entity recognition (NER) are neural models with a conditional random field (CRF) as the final layer. Entities are represented as per-token…
Multiple Word Embeddings for Increased Diversity of Representation
Brian Lester, Daniel Pressel, Amy Hemmeter +2
Most state-of-the-art models in natural language processing (NLP) are neural models built on top of large, pre-trained, contextual language models that generate representations of…
Automatic Data Expansion for Customer-care Spoken Language Understanding
Shahab Jalalvand, Andrej Ljolje, Srinivas Bangalore
Spoken language understanding (SLU) systems are widely used in handling of customer-care calls.A traditional SLU system consists of an acoustic model (AM) and a language model (LM)…
Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation
Nicholas Ruiz, Srinivas Bangalore, John Chen
With the resurgence of chat-based dialog systems in consumer and enterprise applications, there has been much success in developing data-driven and rule-based natural language mode…