Speech recognition challenges in the car navigation industry

Abstract

Until a few decades ago, machines talking and understanding human speech were only the subject of science fiction. Nowadays, Text to Speech (TTS) and Automatic Speech Recognition (ASR) became reality, but they are still being considered to be fancy. Automotive infotainment is a selling point for car manufacturers, it is a symbol of being hi-tech, and car commercials often feature the display of the head unit for a few seconds. As avoiding Driver Distraction has grown a major design aspect, ASR is becoming trendy and almost compulsory. But let us see how far we have gotten. In the first part, this talk will summarize the most popular Speech features in today’s car navigation systems, and will look into the underlying technology, solutions and limitations widely applied in the industry. We will mention typical context designs, dialogue systems and address search, and we will show how the common technology leads to typical HMI solutions. We will point out the possibilities and limitations of on-board and server-based recognition, and consider why we need to resort to exclusively offline solutions for a while in this industry. At this point we will have an overview of the ingredients, so the talk will focus on problematic and sub-optimal ASR features requested by automotive manufacturers, explaining why they negatively affect recognition accuracy. A workaround often leads to troublesome and seemingly unnecessary questions for the user, so it is not easy to compromise. In the last part, we will examine a certain address search scenario which is trivial for users, and is feasible with a server-based ASR, however being an open question when done offline.