Search Results for author:
Found 11 papers, 6 papers with code
Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens
Recent advancements in large language models (LLMs) have driven significant progress in zero-shot text-to-speech (TTS) synthesis.
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and inference-time compute.
Enhancing GNNs with Architecture-Agnostic Graph Transformations: A Systematic Analysis
This study systematically explores the impact of various graph transformations as pre-processing steps on the performance of common GNN architectures across standard datasets.
Single-Codec: Single-Codebook Speech Codec towards High-Performance Speech Generation
The multi-codebook speech codec enables the application of large language models (LLM) in TTS but bottlenecks efficiency and robustness due to multi-sequence prediction.
Disentangling Heterogeneous Knowledge Concept Embedding for Cognitive Diagnosis on Untested Knowledge
Finally, the embeddings will be applied to multiple existing cognitive diagnosis models to infer students' proficiency on UKCs.
Distributed Extended Object Tracking Using Coupled Velocity Model from WLS Perspective
Under the consensus scheme, a distributed WLS filter over a realistic network with ``naive'' node is developed by proper weighting of the priors and measurements.
Distributed Extended Object Tracking Information Filter Over Sensor Networks
This work aims to design a distributed extended object tracking (EOT) system over a realistic network, where both the extent and kinematics are required to retain consensus within the entire network.
Distributed Weighted Least Squares Estimator Based on ADMM
To this end, we first exploit the equivalent relation between the information filter and WLS estimator.
Are You for Real? Detecting Identity Fraud via Dialogue Interactions
In this paper, we focus on identity fraud detection in loan applications and propose to solve this problem with a novel interactive dialogue system which consists of two modules.
Incremental Learning from Scratch for Task-Oriented Dialogue Systems
Clarifying user needs is essential for existing task-oriented dialogue systems.
A Teacher-Student Framework for Maintainable Dialog Manager
Specifically, the {``}student{''} is an extended dialog manager based on a new ontology, and the {``}teacher{''} is existing resources used for guiding the learning process of the {``}student{''}.
