This paper discusses the interpretation of the measurement problem and Qbism in quantum mechanics using the Human Language based Consciousness (HLbC) model proposed by the author. The HLbC model holds that consciousness is generated from physical processes only. It adopts the position that consciousness is generated from physical processes only. 

The HLbC model, as proposed by the author, has been utilized to interpret the varied behaviors manifested by individuals with split-brains. This paper initially provides a succinct overview of the function of the corpus callosum, pivotal to discussions concerning split-brains, along with the distinctive behaviors demonstrated by subjects with split-brains. Subsequently, it elucidates the application of the HLbC model in interpreting the behavior of such individuals. Comparative analyses with normal brain function are then conducted.

This paper interprets subjective psychological time in a model of consciousness called the HLbC model proposed by the authors. Time has an objective physical time and a subjective psychological time. Subjective psychological time is thought to vary in its flow depending on the individual and the situation. For this explanation, this paper introduces surreal numbers into the perception of subjective psychological time.

This paper presents a mathematical proof of the equivalence between the Human Language-based Consciousness (HLbC) model and Bayesian inference, exploring their connection within neural information processing. The HLbC model posits that consciousness emerges through a process involving the observation of external events, the matching of those events to past memories, unconscious action selection, and post-hoc recognition of actions as conscious decisions.

This paper presents a novel framework for measuring consciousness strength based on the Human Language-based Consciousness (HLbC) model. While Integrated Information Theory (IIT) quantifies consciousness via integrated information, the HLbC model views consciousness as a post-hoc process, emphasizing language and probabilistic decision-making.