The advancement of audio-language (AL) multimodal learning tasks has been significant in
recent years, yet the limited size of existing audio-language datasets poses challenges for …

In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

Neural audio codecs are initially introduced to compress audio data into compact codes to
reduce transmission latency. Researchers recently discovered the potential of codecs as …

Generative Pre-trained Transformer (GPT) models have achieved remarkable performance
on various natural language processing tasks, and have shown great potential as …

Audio is an essential part of our life, but creating it often requires expertise and is time-
consuming. Research communities have made great progress over the past year advancing …

While recent large-scale text-to-speech (TTS) models have achieved significant progress,
they still fall short in speech quality, similarity, and prosody. Considering speech intricately …

Recent progress in large-scale zero-shot speech synthesis has been significantly advanced
by language models and diffusion models. However, the generation process of both …

This paper introduces Embarrassingly Easy Text-to-Speech (E2 TTS), a fully non-
autoregressive zero-shot text-to-speech system that offers human-level naturalness and …

Rationality is characterized by logical thinking and decision-making that align with evidence
and logical rules. This quality is essential for effective problem-solving, as it ensures that …

Neural codecs have become crucial to recent speech and audio generation research. In
addition to signal compression capabilities, discrete codecs have also been found to …