Edge computing is an emerging paradigm that offloads the computations and analytics
workloads onto the Internet of Things (IoT) edge devices to accelerate the computation …

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 …

We tackle the task of conditional music generation. We introduce MusicGen, a single
Language Model (LM) that operates over several streams of compressed discrete music …

Large-scale generative models such as GPT and DALL-E have revolutionized the research
community. These models not only generate high fidelity outputs, but are also generalists …

We introduce a language modeling approach for text to speech synthesis (TTS). Specifically,
we train a neural codec language model (called Vall-E) using discrete codes derived from …

Abstract Language models have been successfully used to model natural signals, such as
images, speech, and music. A key component of these models is a high quality neural …

Abstract 3D Semantic Scene Completion (SSC) has emerged as a nascent and pivotal
undertaking in autonomous driving aiming to predict the voxel occupancy within volumetric …

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

Scaling text-to-speech (TTS) to large-scale, multi-speaker, and in-the-wild datasets is
important to capture the diversity in human speech such as speaker identities, prosodies …

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