Measurment of Impact of Environment Acoustics on Speech Recognition Accuracy

This bachelor thesis deals with investigation of impacts of acoustical parameters on automatic speech recognition (ASR) accuracy. Used ASRs were evaluated on Speecon, Temic and LibriSpeech corpuses. This work includes comparison of different versions of these data, which were created using retransmission in several rooms and artificial retransmission using impulse responses. These were created using methods Exponential sine sweep (ESS) and Maximum length sequence (MLS) for real rooms, as well as using Image source model (ISM) method, which generates artificial impulse responses. Output of the thesis is comparison of these types of retransmission. For ESS method, ASR accuracy for different lengths of the excitation signal is examined. Furthermore, the impact of relative position between source and receiver, presence of barriers and directionality of microphones is studied