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 …

This survey paper provides a comprehensive overview of the recent advancements and
challenges in applying large language models to the field of audio signal processing. Audio …

Recently, instruction-following audio-language models have received broad attention for
audio interaction with humans. However, the absence of pre-trained audio models capable …

Large Language models (LLM) have demonstrated the capability to handle a variety of
generative tasks. This paper presents the UniAudio system, which, unlike prior task-specific …

This paper introduces VALL-E 2, the latest advancement in neural codec language models
that marks a milestone in zero-shot text-to-speech synthesis (TTS), achieving human parity …

Audio generation is a major branch of generative AI research. Compared with prior works in
this area that are commonly task-specific with heavy domain knowledge, this paper …

The language model (LM) approach based on acoustic and linguistic prompts, such as
VALL-E, has achieved remarkable progress in the field of zero-shot audio generation …

We introduce a text-to-speech (TTS) model called BASE TTS, which stands for $\textbf {B} $
ig $\textbf {A} $ daptive $\textbf {S} $ treamable TTS with $\textbf {E} $ mergent abilities …

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 …

The sound codec's dual roles in minimizing data transmission latency and serving as
tokenizers underscore its critical importance. Recent years have witnessed significant …