Spirit LM: Meta AI’s Multimodal Model for Seamless Text and Speech Generation

Meta AI's SPIRIT LM is a multimodal foundation model that combines speech and text processing into a single system. It can handle tasks such as automatic speech recognition (ASR), text-to-speech (TTS), speech classification, and expressive speech generation. The model offers two versions: SPIRIT LM BASE and SPIRIT LM EXPRESSIVE, with the latter capturing pitch and style nuances of spoken language. Key features include interleaving text and speech data, few-shot learning across modalities, and multimodal sentiment preservation. Technical architecture is based on LLaMA 2 fine-tuned with both text and speech data. Evaluation shows strong results in comprehension, sentiment preservation, and few-shot learning tasks. Applications span across industries like assistive technologies, content creation, multimodal translation, and sentiment analysis. However, the model faces limitations such as performance degradation in larger models, challenges in speech generation complexity, limited non-English support, added toxicity risks, and trade-offs in expressiveness.