Recent advancements in speech recognition and language technologies have significantly improved their performance across various applications: speech recognition, spoken language understanding, speaker diarization, speech analytics. However,these systems still face challenges when applied “in the wild, e.g. in typical domestic or office-like settings, due to background noise and overlapping speech. These factors hinder the effectiveness of current speech technologies, highlighting a need for further research and development. The project aims to investigate novel speech processing methods to address these challenges, eventually leveraging multimodal language models, to enhance performance in real operational conditions. This research will contribute to the creation of more reliable and trustworthy speech technologies, ultimately improving user experiences and expanding the applicability of these technologies.