SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning

Understand

We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs).

• SIFT-50M is built from publicly available speech corpora, which collectively contain 14K hours of speech, and leverages LLMs along with off-the-shelf expert models.
• The dataset spans five languages, encompassing a diverse range of speech understanding as well as controllable speech generation instructions.
• Using SIFT-50M, we train SIFT-LLM, which outperforms existing speech-text LLMs on instruction-following benchmarks while achieving competitive performance on foundational speech tasks.