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Found 13 papers, 9 papers with code
An Empirical study to understand the Compositional Prowess of Neural Dialog Models
In this work, we examine the problems associated with neural dialog models under the common theme of compositionality.
Exploring Prediction Targets in Masked Pre-Training for Speech Foundation Models
Additionally, prediction targets can vary in the level of detail they encode; targets that encode fine-grained acoustic details are beneficial for denoising tasks, while targets that encode higher-level abstractions are more suited for content-related tasks.
Overview of Robust and Multilingual Automatic Evaluation Metrics for Open-Domain Dialogue Systems at DSTC 11 Track 4
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
Recent Text-to-Speech (TTS) systems trained on reading or acted corpora have achieved near human-level naturalness.
A unified one-shot prosody and speaker conversion system with self-supervised discrete speech units
To address these issues, we devise a cascaded modular system leveraging self-supervised discrete speech units as language representation.
Automatic Evaluation and Moderation of Open-domain Dialogue Systems
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.
Fine-grained style control in Transformer-based Text-to-speech Synthesis
In this paper, we present a novel architecture to realize fine-grained style control on the transformer-based text-to-speech synthesis (TransformerTTS).
Exploring Wav2vec 2.0 fine-tuning for improved speech emotion recognition
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.
Adjusting Image Attributes of Localized Regions with Low-level Dialogue
Our system grounds language on the level of edit operations, and suggests options for a user to choose from.
The Second Conversational Intelligence Challenge (ConvAI2)
We describe the setting and results of the ConvAI2 NeurIPS competition that aims to further the state-of-the-art in open-domain chatbots.
RubyStar: A Non-Task-Oriented Mixture Model Dialog System
RubyStar is a dialog system designed to create "human-like" conversation by combining different response generation strategies.
User Intent Classification using Memory Networks: A Comparative Analysis for a Limited Data Scenario
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.
