Title: TalkPlayData 2: An Agentic Synthetic Data Pipeline for Multimodal  Conversational Music Recommendation
Primary area: datasets and benchmarks
Keywords: music, recsys, dataset, conversational recommendation, LLM

Abstract: We present TalkPlayData 2, a synthetic dataset for multimodal conversational music recommendation generated by an agentic data pipeline. In the proposed pipeline, multiple large language model (LLM) agents are created under various roles with specialized prompts and access to different parts of information, and the chat data is acquired by logging the conversation between the Listener LLM and the Recsys LLM. To cover various conversation scenarios, for each conversation, the Listener LLM is conditioned on a finetuned conversation goal. Finally, all the LLMs are multimodal with audio and images, allowing a simulation of multimodal recommendation and conversation. In the LLM-as-a-judge and subjective evaluation experiments, TalkPlayData 2 achieved the proposed goal in various aspects related to training a generative recommendation model for music.

TL;DR: Use multiple, multimodal LLMs with specialized roles and prompts to synthesize a dataset for conversational music recommendation