Search Results for author: Vikas Bhardwaj

Found 10 papers, 1 papers with code

Building Adaptive Acceptability Classifiers for Neural NLG

no code implementations EMNLP 2021 Soumya Batra, Shashank Jain, Peyman Heidari, Ankit Arun, Catharine Youngs, Xintong Li, Pinar Donmez, Shawn Mei, Shiunzu Kuo, Vikas Bhardwaj, Anuj Kumar, Michael White

We propose a novel framework to train models to classify acceptability of responses generated by natural language generation (NLG) models, improving upon existing sentence transformation and model-based approaches.

Synthetic Data Generation Text Generation

Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings

no code implementations EMNLP 2020 Phillip Keung, Yichao Lu, Julian Salazar, Vikas Bhardwaj

Multilingual contextual embeddings have demonstrated state-of-the-art performance in zero-shot cross-lingual transfer learning, where multilingual BERT is fine-tuned on one source language and evaluated on a different target language.

Model Selection Transfer Learning +1

Attentional Speech Recognition Models Misbehave on Out-of-domain Utterances

1 code implementation12 Feb 2020 Phillip Keung, Wei Niu, Yichao Lu, Julian Salazar, Vikas Bhardwaj

We discuss the problem of echographic transcription in autoregressive sequence-to-sequence attentional architectures for automatic speech recognition, where a model produces very long sequences of repetitive outputs when presented with out-of-domain utterances.

Automatic Speech Recognition Frame

Goal-Oriented End-to-End Conversational Models with Profile Features in a Real-World Setting

no code implementations NAACL 2019 Yichao Lu, Manisha Srivastava, Jared Kramer, Heba Elfardy, Andrea Kahn, Song Wang, Vikas Bhardwaj

To test our models, a customer service agent handles live contacts and at each turn we present the top four model responses and allow the agent to select (and optionally edit) one of the suggestions or to type their own.

Response Generation

A practical approach to dialogue response generation in closed domains

no code implementations28 Mar 2017 Yichao Lu, Phillip Keung, Shaonan Zhang, Jason Sun, Vikas Bhardwaj

We describe a prototype dialogue response generation model for the customer service domain at Amazon.

Response Generation

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