Speaker identity is one of the important characteristics of human speech. In voice
conversion, we change the speaker identity from one to another, while keeping the linguistic …

Generative AI has demonstrated impressive performance in various fields, among which
speech synthesis is an interesting direction. With the diffusion model as the most popular …

Big data analytics (BDA) is a systematic approach for analyzing and identifying different
patterns, relations, and trends within a large volume of data. In this paper, we apply BDA to …

In this paper, a neural network named sequence-to-sequence ConvErsion NeTwork
(SCENT) is presented for acoustic modeling in voice conversion. At training stage, a SCENT …

Accurate and efficient prediction of vacant parking space availability, despite its great
significance, is no easy a task. How to address the noise in the original data and how to …

A short-term traffic flow prediction framework is proposed for urban road networks based on
data-driven methods that mainly include two modules. The first module contains a set of …

The rapid advancement of AI and machine learning has significantly enhanced sound and
acoustic recognition technologies, moving beyond traditional models to more sophisticated …

The voice conversion (VC) system is a well-known approach to improve the communication
efficiency of patients with dysarthria. In this study, we used a gated convolutional neural …

This paper presents methods of making using of text supervision to improve the performance
of sequence-to-sequence (seq2seq) voice conversion. Compared with conventional frame …

For training the sequence-to-sequence voice conversion model, we need to handle an issue
of insufficient data about the number of speech pairs which consist of the same utterance …