Search Results for author: Lazaros Polymenakos

Found 12 papers, 5 papers with code

Data Augmentation for Training Dialog Models Robust to Speech Recognition Errors

no code implementations WS 2020 Longshaokan Wang, Maryam Fazel-Zarandi, Aditya Tiwari, Spyros Matsoukas, Lazaros Polymenakos

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 (ASR) and feed the text to downstream dialog models for natural language understanding and response generation.

Automatic Speech Recognition Data Augmentation +3

Multi-domain Conversation Quality Evaluation via User Satisfaction Estimation

no code implementations18 Nov 2019 Praveen Kumar Bodigutla, Lazaros Polymenakos, Spyros Matsoukas

To address these gaps, we created a new Response Quality annotation scheme, introduced five new domain-independent feature sets and experimented with six machine learning models to estimate User Satisfaction at both turn and dialogue level.

Dialogue Management Management

Learning End-to-End Goal-Oriented Dialog with Maximal User Task Success and Minimal Human Agent Use

1 code implementation TACL 2019 Janarthanan Rajendran, Jatin Ganhotra, Lazaros Polymenakos

In this work, we propose an end-to-end trainable method for neural goal-oriented dialog systems which handles new user behaviors at deployment by transferring the dialog to a human agent intelligently.

Goal-Oriented Dialog

Dialog System Technology Challenge 7

no code implementations11 Jan 2019 Koichiro Yoshino, Chiori Hori, Julien Perez, Luis Fernando D'Haro, Lazaros Polymenakos, Chulaka Gunasekara, Walter S. Lasecki, Jonathan K. Kummerfeld, Michel Galley, Chris Brockett, Jianfeng Gao, Bill Dolan, Xiang Gao, Huda Alamari, Tim K. Marks, Devi Parikh, Dhruv Batra

This paper introduces the Seventh Dialog System Technology Challenges (DSTC), which use shared datasets to explore the problem of building dialog systems.

Learning End-to-End Goal-Oriented Dialog with Multiple Answers

1 code implementation EMNLP 2018 Janarthanan Rajendran, Jatin Ganhotra, Satinder Singh, Lazaros Polymenakos

We also propose a new and more effective testbed, permuted-bAbI dialog tasks, by introducing multiple valid next utterances to the original-bAbI dialog tasks, which allows evaluation of goal-oriented dialog systems in a more realistic setting.

Goal-Oriented Dialog

Knowledge-based end-to-end memory networks

no code implementations23 Apr 2018 Jatin Ganhotra, Lazaros Polymenakos

End-to-end dialog systems have become very popular because they hold the promise of learning directly from human to human dialog interaction.

Goal-Oriented Dialog Retrieval

NE-Table: A Neural key-value table for Named Entities

1 code implementation RANLP 2019 Janarthanan Rajendran, Jatin Ganhotra, Xiaoxiao Guo, Mo Yu, Satinder Singh, Lazaros Polymenakos

Many Natural Language Processing (NLP) tasks depend on using Named Entities (NEs) that are contained in texts and in external knowledge sources.

Goal-Oriented Dialog Question Answering +2

Addressee and Response Selection in Multi-Party Conversations with Speaker Interaction RNNs

1 code implementation12 Sep 2017 Rui Zhang, Honglak Lee, Lazaros Polymenakos, Dragomir Radev

In this paper, we study the problem of addressee and response selection in multi-party conversations.

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