Performance against Number of Labels. Recall that the AudioCaps dataset was curated from the
annotations of the audio classiﬁcation task in the AudioSet dataset. The text prompts in AudioCaps
can thus be paired with the discrete class labels of AudioSet. The AudioSet dataset contains a
total of 632 audio event classes. For instance, A woman and a baby are having a conversation and
its corresponding audio clip has the following three labels: Speech, Child speech kid speaking, Inside
small room. We group instances having one label, two labels, and multiple (two or more) labels
in AudioCaps and evaluate the generated audios across the objective metrics. We report the result
of the experiment in Table 4. TANGO outperforms AudioLDM models across all the objective
metrics for audio generation from texts with one label or two labels. For texts with multiple labels,
AudioLDM achieves a better KL divergence score and TANGO achieves better FD and FAD scores.
Text-to-Audio Generation using Instruction-Tuned LLM and Latent Diffusion Model