Search Results for author: Alexander Rudnicky

Found 12 papers, 9 papers with code

An Empirical study to understand the Compositional Prowess of Neural Dialog Models

1 code implementation insights (ACL) 2022 Vinayshekhar Kumar, Vaibhav Kumar, Mukul Bhutani, Alexander Rudnicky

In this work, we examine the problems associated with neural dialog models under the common theme of compositionality.

Overview of Robust and Multilingual Automatic Evaluation Metrics for Open-Domain Dialogue Systems at DSTC 11 Track 4

1 code implementation22 Jun 2023 Mario Rodríguez-Cantelar, Chen Zhang, Chengguang Tang, Ke Shi, Sarik Ghazarian, João Sedoc, Luis Fernando D'Haro, Alexander Rudnicky

The advent and fast development of neural networks have revolutionized the research on dialogue systems and subsequently have triggered various challenges regarding their automatic evaluation.

A Vector Quantized Approach for Text to Speech Synthesis on Real-World Spontaneous Speech

1 code implementation8 Feb 2023 Li-Wei Chen, Shinji Watanabe, Alexander Rudnicky

Recent Text-to-Speech (TTS) systems trained on reading or acted corpora have achieved near human-level naturalness.

Code Generation Speech Synthesis +1

A unified one-shot prosody and speaker conversion system with self-supervised discrete speech units

1 code implementation12 Nov 2022 Li-Wei Chen, Shinji Watanabe, Alexander Rudnicky

To address these issues, we devise a cascaded modular system leveraging self-supervised discrete speech units as language representation.

Voice Conversion

Automatic Evaluation and Moderation of Open-domain Dialogue Systems

2 code implementations3 Nov 2021 Chen Zhang, João Sedoc, Luis Fernando D'Haro, Rafael Banchs, Alexander Rudnicky

The development of Open-Domain Dialogue Systems (ODS)is a trending topic due to the large number of research challenges, large societal and business impact, and advances in the underlying technology.

Chatbot Dialogue Evaluation

Fine-grained style control in Transformer-based Text-to-speech Synthesis

1 code implementation12 Oct 2021 Li-Wei Chen, Alexander Rudnicky

In this paper, we present a novel architecture to realize fine-grained style control on the transformer-based text-to-speech synthesis (TransformerTTS).

Inductive Bias Speech Synthesis +1

Exploring Wav2vec 2.0 fine-tuning for improved speech emotion recognition

1 code implementation12 Oct 2021 Li-Wei Chen, Alexander Rudnicky

While Wav2Vec 2. 0 has been proposed for speech recognition (ASR), it can also be used for speech emotion recognition (SER); its performance can be significantly improved using different fine-tuning strategies.

Speech Emotion Recognition speech-recognition +1

RubyStar: A Non-Task-Oriented Mixture Model Dialog System

no code implementations8 Nov 2017 Huiting Liu, Tao Lin, Hanfei Sun, Weijian Lin, Chih-Wei Chang, Teng Zhong, Alexander Rudnicky

RubyStar is a dialog system designed to create "human-like" conversation by combining different response generation strategies.

Question Answering Response Generation +1

User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario

no code implementations19 Jun 2017 Arjun Bhardwaj, Alexander Rudnicky

Since the classifier is meant to serve as a module in a practical dialog system, it needs to be able to work with limited training data and incorporate new data on the fly.

General Classification intent-classification +3

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