A Simple Model of Speech Communication and its Application to Intelligibility Enhancement

Abstract

Abstract-We introduce a model of communication that includes noise inherent in the message production process as well as noise inherent in the message interpretation process. The production and interpretation noise processes have a fixed signal-to-noise ratio. The resulting system is a simple but effective model of human communication. The model naturally leads to a method to enhance the intelligibility of speech rendered in a noisy environment. State-of-the-art experimental results confirm the practical value of the model.

An intelligibility metric based on a simple model of speech communication

“…We adopt the model presented in [17], which considers the transmission of a message from a talker to a listener and assumes a noisy speech production process.…”

“…Furthermore, we assume that P is zero mean and that P and M are statistically independent. The logarithm in (5) is applied so that P has an additive nature consistent with the model in [17]. Since the logarithm is an invertible function, we can transform the signals without affecting the information rate.…”

“…Figure 3 plot the listening test scores against the proposed intelligibility metric and STOI for each experiment. The mapping functions (17) and (18) are also included. The plots show that there is a strong relationship between listening test scores and the proposed intelligibility metric.…”

“…First, several studies have suggested that IT could provide a unified point of view. In [16] and [17] it was observed that the AI resembles the Shannon capacity of a memoryless Gaussian channel, and in [14] it was shown that STOI is related to the average amount of information shared between the temporal envelopes of clean and distorted speech signals. Second, IT provides a powerful theoretical framework.…”

“…In [17] a simple but effective model of speech communication was presented that includes variability inherent in the speech production process. It was argued that this variability, called 'production noise', causes the usefulness of a communication channel to saturate.…”