We present the use of stethoscope and silicon NAM (nonaudible murmur) microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker’s ear and can capture not only normal (audible) speech, but also very quietly uttered speech (nonaudible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems w...

Automatic recognition of the speech of children is a challenging topic in computer-based speech recognition systems. Conventional feature extraction method namely Mel-frequency cepstral coefficient (MFCC) is not efficient for children’s speech recognition. This paper proposes a novel fuzzy-based discriminative feature representation to address the recognition of Malay vowels uttered by children...

In most of the practical applications of Automatic Speech Recognition (ASR), the input speech is contaminated by a background noise. This strongly degrades the performance of speech recognizers (Gong, 1995; Cole et al., 1995; Torre et al., 2000). The reduction of the accuracy could make unpractical the use of ASR technology in applications that must work in real conditions, where the input spee...

Language learners are known to perform best in one-on-one interactive situations in which they receive optimal corrective feedback. However, one-on-one tutoring by trained language instructors is costly and therefore not feasible for the majority of language learners. This particularly applies to oral proficiency, which requires intensive tutoring. Computer Assisted Language Learning (CALL) sys...

In this article I will discuss the possible use of automatic speech recognition (ASR) for training students to improve their accents in a foreign language. Principles of good language training as well as the limits of the use of Automatic Speech Recognition (ASR) and how to deal with them will be discussed first. I will then use the example of the Carnegie Mellon FLUENCY system to show concrete...

Previous studies have shown that infant-directed speech ('motherese') exhibits overemphasized acoustic properties which may facilitate the acquisition of phonetic categories by infant learners. It has been suggested that the use of infant-directed data for training automatic speech recognition systems might also enhance the automatic learning and discrimination of phonetic categories. This stud...

In this paper, we introduce a new corpus of oral cancer speech and present our study on the automatic recognition analysis speech. A two-hour English dataset is collected from YouTube. Formulated as low-resource ASR task, investigate three acoustic modelling approaches that previously have worked well with scenarios using two different architectures; hybrid architecture transformer-based end-to...