We present an overview of the most comon techniques used in automatic speech recognition to adapt a general system to a different environment (known as cross-task adaptation) such as in air traffic control systems (ATC). The conditions present in ATC are very specific: very spontaneous, the presence of noise, and high speech speech. So, with a typical speech recognizer, the recognition results are unsatisfactory. We have to decide on the best option for the modeling: to develop acoustic models specific to those conditions from scratch using the data available for the new envirnoment, or to carry out cross-task adaptation starting from reliable HMM models (usually requiring less data in the target domain).
|