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Automatic Speech Recognition

This special issue belongs to the section “Acoustics and Vibrations“.

Special Issue Information

Dear Colleagues,

Major progress is being published regularly on both the technology and exploitation of automatic speech recognition (ASR). However, there are still technological barriers to flexible solutions and user satisfaction under some circumstances. This is related to several factors, such as sensitivity to the environment (background noise), or weak representation of grammatical and semantic knowledge. Current research is also emphasizing deficiencies in dealing with variation naturally present in speech. For instance, the lack of robustness to foreign accents precludes use by specific populations. There are actually many factors affecting speech realization: regional, sociolinguistic, or related to the environment or the speaker themselves. These create a wide range of variations that may not be modeled correctly (speaker, gender, emotion, speaking rate, vocal effort, regional accent, speaking style, non-stationarity, etc.), especially when resources for system training are scarce. We are interested in articles that explore robust ASR systems. Potential topics include but are not limited to the following:

  • Automatic speech segmentation and phoneme detection;
  • Automatic speech recognition with noised speech;
  • Automatic speech translation;
  • Automatic classification of emotions in speech;
  • Multimodal speech recognition with video or physiological signals;

Dr. Lijiang Chen
Guest Editor

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Keywords

  • speech recognition
  • noise reduction
  • emotion recognition
  • environment independence
  • acoustic model

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Appl. Sci. - ISSN 2076-3417