In an era defined by the explosive growth of data and rapid technological advancements,
Multimodal Large Language Models (MLLMs) stand at the forefront of artificial intelligence …

We introduce AudioLM, a framework for high-quality audio generation with long-term
consistency. AudioLM maps the input audio to a sequence of discrete tokens and casts …

Large language models (LLMs) have exhibited remarkable capabilities across a variety of
domains and tasks, challenging our understanding of learning and cognition. Despite the …

Various applications of voice synthesis have been developed independently despite the fact
that they generate" voice" as output in common. In addition, the majority of voice synthesis …

Recent advancements in spoken dialogue models, exemplified by systems like GPT-4o,
have captured significant attention in the speech domain. Compared to traditional three-tier …

Recent work in spoken language modeling shows the possibility of learning a language
unsupervisedly from raw audio without any text labels. The approach relies first on …

Prompting has become a practical method for utilizing pre-trained language models (LMs).
This approach offers several advantages. It allows an LM to adapt to new tasks with minimal …

Human speech can be characterized by different components, including semantic content,
speaker identity and prosodic information. Significant progress has been made in …

Voice user interfaces and digital assistants are rapidly entering our lives and becoming
singular touch points spanning our devices. These always-on services capture and transmit …

AfterLearnER (After Learning Evolutionary Retrofitting) consists in applying non-
differentiable optimization, including evolutionary methods, to refine fully-trained machine …