We present an overview of the most common techniques used in automatic speech recognition to adapt a general system to a different environment (known as cross-task adaptation) such as in an air traffic control system (ATC). The conditions present in ATC are very specific: very spontaneous, the presence of noise, and high speed 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 environment, or to carry out cross-task adaptation starting from reliable HMM models (usually requiring less data in the target domain). We begin with a description of the main techniques considered for cross-task adaptation, namely maximum a posteriori (MAP), maximum likelihood linear regression (MLLR), and the two together. We have applied each in two speech recognizers for air traffic control tasks, one for spontaneous speech and the other for a command interface. We show the performance of these techniques and compare them with the development of a new system from scratch. We also show the results obtained for speaker adaptation using a variable amount of adaptation data. The main conclusion is that MLLR can outperform MAP when a large number of transforms is used, and MLLR followed by MAP is the best option. All of these techniques are better than developing a new system from scratch, showing the effectiveness of mean and variance adaptation


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Air traffic control speech recognition system cross-task & speaker adaptation


    Contributors:


    Publication date :

    2006-09-01


    Size :

    940558 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Speaker Adaptation Through Spectral Transformation for HMM Based Speech Recognition

    Choi, H. C. / King, R. W. / IEEE; Hong Kong Chapter of Signal Processing | British Library Conference Proceedings | 1994



    Minimum effort adaptation of automatic speech recognition system in air traffic management

    Mrinmoy Bhattacharjee / Petr Motlicek / Srikanth Madikeri et al. | DOAJ | 2025

    Free access

    Mathematical Analysis and Speaker-Independent Speech Recognition

    Gur'yanov, A. E. | British Library Online Contents | 1996