A Review of Accent-Based Automatic Speech Recognition Models for E-Learning Environment

The adoption of electronics learning (e-learning) as a method of disseminating knowledge in the global educational system is growing at a rapid rate, and has created a shift in the knowledge acquisition methods from the conventional classrooms and tutors to the distributed e-learning technique that enables access to various learning resources much more conveniently and flexibly. However, notwithstanding the adaptive advantages of learner-centric contents of e-learning programmes, the distributed e-learning environment has unconsciously adopted few international languages as the languages of communication among the participants despite the various accents (mother language influence) among these participants. Adjusting to and accommodating these various accents has brought about the introduction of accents-based automatic speech recognition into the e-learning to resolve the effects of the accent differences. This paper reviews over 50 research papers to determine the development so far made in the design and implementation of accents-based automatic recognition models for the purpose of e-learning between year 2001 and 2021. The analysis of the review shows that 50% of the models reviewed adopted English language, 46.50% adopted the major Chinese and Indian languages and 3.50% adopted Swedish language as the mode of communication. It is therefore discovered that majority of the ASR models are centred on the European, American and Asian accents, while unconsciously excluding the various accents peculiarities associated with the less technologically resourced continents

Automatic Speech Recognition for Low-resource Languages and Accents Using Multilingual and Crosslingual Information

This thesis explores methods to rapidly bootstrap automatic speech recognition systems for languages, which lack resources for speech and language processing. We focus on finding approaches which allow using data from multiple languages to improve the performance for those languages on different levels, such as feature extraction, acoustic modeling and language modeling. Under application aspects, this thesis also includes research work on non-native and Code-Switching speech

The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

A Sound Approach to Language Matters: In Honor of Ocke-Schwen Bohn

The contributions in this Festschrift were written by Ocke’s current and former PhD-students, colleagues and research collaborators. The Festschrift is divided into six sections, moving from the smallest building blocks of language, through gradually expanding objects of linguistic inquiry to the highest levels of description - all of which have formed a part of Ocke’s career, in connection with his teaching and/or his academic productions: “Segments”, “Perception of Accent”, “Between Sounds and Graphemes”, “Prosody”, “Morphology and Syntax” and “Second Language Acquisition”. Each one of these illustrates a sound approach to language matters

THE USE OF SEGMENTATION CUES IN SECOND LANGUAGE LEARNERS OF ENGLISH

This dissertation project examined the influence of language typology on the use of segmentation cues by second language (L2) learners of English. Previous research has shown that native English speakers rely more on sentence context and lexical knowledge than segmental (i.e. phonotactics or acoustic-phonetics) or prosodic cues (e.g., word stresss) in native language (L1) segmentation. However, L2 learners may rely more on segmental and prosodic cues to identify word boundaries in L2 speech since it may require high lexical and syntactic proficiency in order to use lexical cues efficiently. The goal of this dissertation was to provide empirical evidence for the Revised Framework for L2 Segmentation (RFL2) which describes the relative importance of different levels of segmentation cues. Four experiments were carried out to test the hypotheses made by RFL2. Participants consisted of four language groups including native English speakers and L2 learners of English with Mandarin, Korean, or Spanish L1s. Experiment 1 compared the use of stress cues and lexical knowledge while Experiment 2 compared the use of phonotactic cues and lexical knowledge. Experiment 3 compared the use of phonotactic cues and semantic cues while Experiment 4 compared the use of stress cues and sentence context. Results showed that L2 learners rely more on segmental cues than lexical knowledge or semantic cues. L2 learners showed cue interaction in both lexical and sublexical levels whereas native speakers appeared to use the cues independently. In general, L2 learners appeared to have acquired sensitivity to the segmentation cues used in L2, although they still showed difficulty with specific aspects in each cue based on L1 characteristics. The results provided partial support for RFL2 in which L2 learners' use of sublexical cues was influenced by L1 typology. The current dissertation has important pedagogical implication as findings may help identify cues that can facilitate L2 speech segmentation and comprehension