Large Language Models (LLMs) have revolutionized a wide range of applications with their
strong human-like understanding and creativity. Due to the continuously growing model size …

In recent years, end-to-end automatic speech recognition (ASR) systems have proven
themselves remarkably accurate and performant, but these systems still have a significant …

Recent advances in deep learning and automatic speech recognition have improved the
accuracy of end-to-end speech recognition systems, but recognition of personal content …

With increasingly more powerful compute capabilities and resources in today's devices,
traditionally compute-intensive automatic speech recognition (ASR) has been moving from …

Large language models (LLMs) have shown superb capability of modeling multimodal
signals including audio and text, allowing the model to generate spoken or textual response …

Automatic speech recognition (ASR) technology has reached a mature level, and improving
performance in data-scarce scenarios has become a key research focus. In this study, we …

In recent years, the evolution of end-to-end (E2E) automatic speech recognition (ASR)
models has been remarkable, largely due to advances in deep learning architectures like …

Voice assistants increasingly use on-device Automatic Speech Recognition (ASR) to ensure
speed and privacy. However, due to resource constraints on the device, queries pertaining …

Research on adversarial attacks mainly focuses on reducing the amplitude of disturbances,
increasing the success rate of attacks, and improving attack efficiency. However, the …

This master's thesis investigates the practical application of Automatic Speech Recognition
(ASR) technology, namely the Whisper model, for transcribing Norwegian police interviews …