Building on the foundations of language modeling in natural language processing, Next
Token Prediction (NTP) has evolved into a versatile training objective for machine learning …

This paper introduces F5-TTS, a fully non-autoregressive text-to-speech system based on
flow matching with Diffusion Transformer (DiT). Without requiring complex designs such as …

Text-to-speech (TTS), also known as speech synthesis, is a prominent research area that
aims to generate natural-sounding human speech from text. Recently, with the increasing …

Multimodal generative models require a unified approach to handle both discrete data (eg,
text and code) and continuous data (eg, image, audio, video). In this work, we propose …

Recently, Text-to-speech (TTS) models based on large language models (LLMs) that
translate natural language text into sequences of discrete audio tokens have gained great …

In our previous work, we introduced CosyVoice, a multilingual speech synthesis model
based on supervised discrete speech tokens. By employing progressive semantic decoding …

Large-scale speech generation models have achieved impressive performance in the zero-
shot voice clone tasks relying on large-scale datasets. However, exploring how to achieve …

Removing modeling constraints and unifying architectures across domains has been a key
driver of the recent progress in training large multimodal models. However, most of these …

The rapid development of large-scale text-to-speech (TTS) models has led to significant
advancements in modeling diverse speaker prosody and voices. However, these models …

We introduce Audio-Agent, a multimodal framework for audio generation, editing and
composition based on text or video inputs. Conventional approaches for text-to-audio (TTA) …