The project is divided into three parts:

• Prediction and Modelling of Noise and its Diversity in Mobile Environments (Southampton University)

• Speaker Modelling, Adaptation and Identification in Noise in Mobile Environments (UEA, Norwich)

• Enhancement of Noisy Speech  in Mobile Environments (Brunel University)

Mobile phones are often used in noisy outdoor environments such as a noisy street, airports, cafe, or in a moving car/train. The quality and intelligibility of speech can be severely degraded by the ambient noise. Therefore noise reduction is an increasingly important aspect of improving the quality of service (QoS) and reliability of speech communication. With the increasingly deployment of speech recognition and voice-based systems across a wide range of multimedia mobile services, it is important to the users and providers of mobile phones that speech communication and access to voice recognition systems is not impaired by noise. Noise degrades the accuracy of automatic speech recognition even for such modest tasks as name dialling, automatic directory enquiry, or voice control of the accessories in a moving car. Furthermore, the future generation of very low bit rate coders will increasingly depend on correct speech classification and accurate estimation of speech parameters for improved performance. The aim of this proposal is to develop an integrated system for both speech enhancement and speech recognition. This will be achieved through the development of a unified speech model for both speech recognition and synthesis/reconstruction, together with decision-tree predictive models of non-stationary noise sources typically encountered in mobile environments.