Decoder Only Architecture

Decoder-only architectures are a rapidly developing area in large language model (LLM) research, focusing on streamlining natural language processing tasks by eliminating the encoder component traditionally used for input processing. Current research emphasizes applying this architecture to various speech-related tasks, including speech recognition, speech-to-text translation, and simultaneous machine translation, often incorporating techniques like CTC prompts and parameter-efficient fine-tuning to improve efficiency and performance. This approach offers potential advantages in speed, memory usage, and ease of integration with existing LLMs, leading to more efficient and potentially more powerful models for a wide range of applications. The resulting improvements in speed and resource efficiency are particularly significant for real-time applications like streaming speech recognition and simultaneous translation.