Sommelier: Scalable Open Multi-turn Audio Pre-processing for Full-duplex Speech Language Models

1. 1Developing full-duplex speech language models requires high-quality multi-speaker conversational data
2. 2Existing large-scale resources are predominantly single-speaker or limited in volume
3. 3Sommelier addresses the complex dynamics of natural dialogue by providing scalable open multi-turn audio pre-processing
4. 4Practitioners can apply Sommelier to improve the performance of their speech language models

AI engineers and researchers working on speech language models can benefit from Sommelier as it enables real-time natural human-computer interaction, and data scientists can utilize it for high-quality multi-speaker conversational data

💡 Sommelier addresses the scarcity of high-quality multi-speaker conversational data for full-duplex speech language models

💡 Sommelier enables real-time human-computer interaction with scalable open multi-turn audio pre-processing #SLMs #AI