An In-Car Speech Recognition System for Disabled Drivers

Abstract

Automatic Speech Recognition (ASR) is becoming a standard in nowadays cars. However, ASR in cars is usually restricted to activities not directly influencing the driving process. Thus, the voice-controlled functions can rather be classified as comfort functions, e.g. controlling the air condition, the navigation and entertainment system or even the mobile phone of the driver. Obviously this usage of an ASR system could be extended in two directions: On the one side, the speech recognition system could be used to control secondary functions in the car like lights, windscreen wipers or windows. On the other side, the comfort functions could be enriched by utilizing services like weather inquiries, SMS dictation or online traffic information. Compared to todays usage these extensions require a different approach than the one employed today. Controlling secondary functions in the car by voice demands the usage of a very reliable, real-time, local ASR. At the same time a large vocabulary ASR system is required for comfort functions like dictation of messages.

In this paper, we describe our efforts towards a hybrid speech recognition system to control secondary functions in the car. We also provide an extended comfort functionality to the driver. The hybrid speech recognition system contains a fast, grammar-based, embedded recognizer and a remote, server-based, LM-based, large vocabulary ASR system. We will analyze different aspects of such a design and the integration of it into a car. The main focus of the paper will be on maximizing the reliability of the embedded recognizer and designing an algorithm for switching dynamically between the embedded recognizer and the server-based ASR system.