3 Methodology

This section provides details of Qwen-Audio and Qwen-Audio-Chat, which are designed for universal audio
understanding and flexible interaction based on human instructions. The model structure of Qwen-Audio and
Qwen-Audio-Chat is first presented in Section 3.1. The training process of our models consists of two stages:
multitask pretraining and supervised fine-tuning. We describe the training of Qwen-Audio via multitask
learning in Section 3.2. Then, we describe Qwen-Audio-Chat with supervised fine-tuning in Section 3.3 ,
which enables flexible human interaction.

3.1 Model Architecture
The architecture of Qwen-Audio models is depicted in Figure 3. Qwen-Audio contains an audio encoder and
a large language model. Given the paired data (a, x), where the a and x denote the audio sequences and
text sequences, the training objective is to maximize the next text token probability as
Qwen-Audio