Gaps to Bridge in Speech Technology

Although recently there has been significant progress in the general usage and acceptance of speech technology in several developed countries there are still major gaps that prevent the majority of possible users from daily use of speech technology-based solutions. In this paper some of them are listed and some directions for bridging these gaps are proposed. Perhaps the most important gap is the "Black box" thinking of software developers. They suppose that inputting text into a text-to-speech (TTS) system will result in voice output that is relevant to the given context of the application. In case of automatic speech recognition (ASR) they wait for accurate text transcription (even punctuation). It is ignored that even humans are strongly influenced by a priori knowledge of the context, the communication partners, etc. For example by serially combining ASR + machine translation + TTS in a speech-to-speech translation system a male speaker at a slow speaking rate might be represented by a fast female voice at the other end. The science of semantic modelling is still in its infancy. In order to produce successful applications researchers of speech technology should find ways to build-in the a priori knowledge into the application environment, adapt their technologies and interfaces to the given scenario. This leads us to the gap between generic and domain specific solutions. For example intelligibility and speaking rate variability are the most important TTS evaluation factors for visually impaired users while human-like announcements at a standard rate and speaking style are required for railway station information systems. An increasing gap is being built between "large" languages/markets and "small" ones. Another gap is the one between closed and open application environments. For example there is hardly any mobile operating system that allows TTS output re-direction into a live telephone conversation. That is a basic need for rehabilitation applications of speech impaired people. Creating an open platform where "smaller" and "bigger" players of the field could equally plug-in their engines/solutions at proper quality assurance and with a fair share of income could help the situation. In the paper some examples are given about how our teams at BME TMIT try to bridge the gaps listed.