We introduce Moshi, a speech-text foundation model and full-duplex spoken dialogue
framework. Current systems for spoken dialogue rely on pipelines of independent …

The revolutionary breakthroughs in Machine Learning (ML) and Artificial Intelligence (AI) are
extensively being harnessed across a diverse range of domains, eg, forensic science …

Abstract Video-to-audio (V2A) generation leverages visual-only video features to render
plausible sounds that match the scene. Importantly, the generated sound onsets should …

This work proposes FireRedTTS, a foundation text-to-speech framework, to meet the
growing demands for personalized and diverse generative speech applications. The …

Large language models (LLM)-based speech synthesis has been widely adopted in zero-
shot speech synthesis. However, they require a large-scale data and possess the same …

This paper proposes Fre-Painter, a high-fidelity audio super-resolution system that utilizes
robust speech representation learning with various masking strategies. Recently, masked …

Recent advances in generative models that iteratively synthesize audio clips sparked great
success to text-to-audio synthesis (TTA), but with the cost of slow synthesis speed and heavy …

Diffusion-based audio and music generation models commonly generate music by
constructing an image representation of audio (eg, a mel-spectrogram) and then converting …

Speech Super-Resolution (SSR) is a task of enhancing low-resolution speech signals by
restoring missing high-frequency components. Conventional approaches typically …

Vibravox is a dataset compliant with the General Data Protection Regulation (GDPR)
containing audio recordings using five different body-conduction audio sensors: two in-ear …