---
license: mit
datasets:
- openslr/librispeech_asr
language:
- en
base_model:
- HuggingFaceTB/SmolLM2-360M-Instruct
tags:
- audio
- speech
- tts
- asr
- unified_model
pipeline_tag: any-to-any
library_name: transformers
---

## 1. Introduction

This work introduces MonoSpeech, a novel approach that integrates autoregression and flow matching 
within a transformer-based framework for speech unified understanding and generation. 
MonoSpeech is designed to achieve both speech comprehension and generation capabilities through a unified model trained in a single stage. 
Our experiments demonstrate that MonoSpeech delivers strong performance for both automatic speech recognition and zero-shot speech synthesis tasks. 
By combining autoregression and flow matching, MonoSpeech establishes a foundation for expanding to additional audio understanding and generation tasks using the paradigm in the future.

[**Github Repository**](https://github.com/gwh22/MonoSpeech)

<div align="center">
<img alt="image" src="assets/MonoSpeech.jpg" style="width:90%;">
</div>



## 2. Quick Start

Please refer to [**Github Repository**](https://github.com/gwh22/Univoice)