Speech Recognition and Listening Effort of Meaningful Sentences Using Synthetic Speech

Abstract

Speech-recognition tests are an important component of audiology. However, the development of such tests can be time consuming. The aim of this study was to investigate whether a Text-To-Speech (TTS) system can reduce the cost of development, and whether comparable results can be achieved in terms of speech recognition and listening effort. For this, the everyday sentences of the German Göttingen sentence test were synthesized for both a female and a male speaker using a TTS system. In a preliminary study, this system was rated as good, but worse than the natural reference. Due to the Covid-19 pandemic, the measurements took place online. Each set of speech material was presented at three fixed signal-to-noise ratios. The participants’ responses were recorded and analyzed offline. Compared to the natural speech, the adjusted psychometric functions for the synthetic speech, independent of the speaker, resulted in an improvement of the speech-recognition threshold (SRT) by approximately 1.2 dB. The slopes, which were independent of the speaker, were about 15 percentage points per dB. The time periods between the end of the stimulus presentation and the beginning of the verbal response (verbal response time) were comparable for all speakers, suggesting no difference in listening effort. The SRT values obtained in the online measurement for the natural speech were comparable to published data. In summary, the time and effort for the development of speech-recognition tests may be significantly reduced by using a TTS system. This finding provides the opportunity to develop new speech tests with a large amount of speech material.