Methods for pronunciation assessment in computer aided language learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 149-176).Learning a foreign language is a challenging endeavor that entails acquiring a wide range of new knowledge including words, grammar, gestures, sounds, etc. Mastering these skills all require extensive practice by the learner and opportunities may not always be available. Computer Aided Language Learning (CALL) systems provide non-threatening environments where foreign language skills can be practiced where ever and whenever a student desires. These systems often have several technologies to identify the different types of errors made by a student. This thesis focuses on the problem of identifying mispronunciations made by a foreign language student using a CALL system. We make several assumptions about the nature of the learning activity: it takes place using a dialogue system, it is a task- or game-oriented activity, the student should not be interrupted by the pronunciation feedback system, and that the goal of the feedback system is to identify severe mispronunciations with high reliability. Detecting mispronunciations requires a corpus of speech with human judgements of pronunciation quality. Typical approaches to collecting such a corpus use an expert phonetician to both phonetically transcribe and assign judgements of quality to each phone in a corpus. This is time consuming and expensive. It also places an extra burden on the transcriber. We describe a novel method for obtaining phone level judgements of pronunciation quality by utilizing non-expert, crowd-sourced, word level judgements of pronunciation. Foreign language learners typically exhibit high variation and pronunciation shapes distinct from native speakers that make analysis for mispronunciation difficult. We detail a simple, but effective method for transforming the vowel space of non-native speakers to make mispronunciation detection more robust and accurate. We show that this transformation not only enhances performance on a simple classification task, but also results in distributions that can be better exploited for mispronunciation detection. This transformation of the vowel is exploited to train a mispronunciation detector using a variety of features derived from acoustic model scores and vowel class distributions. We confirm that the transformation technique results in a more robust and accurate identification of mispronunciations than traditional acoustic models.by Mitchell A. Peabody.Ph.D

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

Computer analysis of children's non-native English speech for language learning and assessment

Children's ASR appears to be more challenging than adults' and it's even more difficult when it comes to non-native children's speech. This research investigates different techniques to compensate for the effects of non-native and children on the performance of ASR systems. The study mainly utilises hybrid DNN-HMM systems with conventional DNNs, LSTMs and more advanced TDNN models. This work uses the CALL-ST corpus and TLT-school corpus to study children's non-native English speech. Initially, data augmentation was explored on the CALL-ST corpus to address the lack of data problem using the AMI corpus and PF-STAR German corpus. Feature selection, acoustic model adaptation and selection were also investigated on CALL-ST. More aspects of the ASR system, including pronunciation modelling, acoustic modelling, language modelling and system fusion, were explored on the TLT-school corpus as this corpus has a bigger amount of data. Then, the relationships between the CALL-ST and TLT-school corpora were studied and utilised to improve ASR performance. The other part of the present work is text processing for non-native children's English speech. We focused on providing accept/reject feedback to learners based on the text generated by the ASR system from learners' spoken responses. A rule-based and a machine learning-based system were proposed for making the judgement, several aspects of the systems were evaluated. The influence of the ASR system on the text processing system was explored

Design and evaluation of mobile computer-assisted pronunciation training tools for second language learning

The quality of speech technology (automatic speech recognition, ASR, and textto- speech, TTS) has considerably improved and, consequently, an increasing number of computer-assisted pronunciation (CAPT) tools has included it. However, pronunciation is one area of teaching that has not been developed enough since there is scarce empirical evidence assessing the effectiveness of tools and games that include speech technology in the field of pronunciation training and teaching. This PhD thesis addresses the design and validation of an innovative CAPT system for smart devices for training second language (L2) pronunciation. Particularly, it aims to improve learner’s L2 pronunciation at the segmental level with a specific set of methodological choices, such as learner’s first and second language connection (L1– L2), minimal pairs, a training cycle of exposure–perception–production, individualistic and social approaches, and the inclusion of ASR and TTS technology. The experimental research conducted applying these methodological choices with real users validates the efficiency of the CAPT prototypes developed for the four main experiments of this dissertation. Data is automatically gathered by the CAPT systems to give an immediate specific feedback to users and to analyze all results. The protocols, metrics, algorithms, and methods necessary to statistically analyze and discuss the results are also detailed. The two main L2 tested during the experimental procedure are American English and Spanish. The different CAPT prototypes designed and validated in this thesis, and the methodological choices that they implement, allow to accurately measuring the relative pronunciation improvement of the individuals who trained with them. Both rater’s subjective scores and CAPT’s objective scores show a strong correlation, being useful in the future to be able to assess a large amount of data and reducing human costs. Results also show an intensive practice supported by a significant number of activities carried out. In the case of the controlled experiments, students who worked with the CAPT tool achieved better pronunciation improvement values than their peers in the traditional in-classroom instruction group. In the case of the challenge-based CAPT learning game proposed, the most active players in the competition kept on playing until the end and achieved significant pronunciation improvement results.Departamento de Informática (Arquitectura y Tecnología de Computadores, Ciencias de la Computación e Inteligencia Artificial, Lenguajes y Sistemas Informáticos)Doctorado en Informátic

WHERE IS THE LOCUS OF DIFFICULTY IN RECOGNIZING FOREIGN-ACCENTED WORDS? NEIGHBORHOOD DENSITY AND PHONOTACTIC PROBABILITY EFFECTS ON THE RECOGNITION OF FOREIGN-ACCENTED WORDS BY NATIVE ENGLISH LISTENERS

This series of experiments (1) examined whether native listeners experience recognition difficulty in all kinds of foreign-accented words or only in a subset of words with certain lexical and sub-lexical characteristics-- neighborhood density and phonotactic probability; (2) identified the locus of foreign-accented word recognition difficulty, and (3) investigated how accent-induced mismatches impact the lexical retrieval process. Experiments 1 and 4 examined the recognition of native-produced and foreign-accented words varying in neighborhood density with auditory lexical decision and perceptual identification tasks respectively, which emphasize the lexical level of processing. Findings from Experiment 1 revealed increased accent-induced processing cost in reaction times, especially for words with many similar sounding words, implying that native listeners increase their reliance on top-down lexical knowledge during foreign-accented word recognition. Analysis of perception errors from Experiment 4 found the misperceptions in the foreign-accented condition to be more similar to the target words than those in the native-produced condition. This suggests that accent-induced mismatches tend to activate similar sounding words as alternative word candidates, which possibly pose increased lexical competition for the target word and result in greater processing costs for foreign-accented word recognition at the lexical level. Experiments 2 and 3 examined the sub-lexical processing of the foreign-accented words varying in neighborhood density and phonotactic probability respectively with a same-different matching task, which emphasizes the sub-lexical level of processing. Findings from both experiments revealed no extra processing costs , in either reaction times or accuracy rates, for the foreign-accented stimuli, implying that the sub-lexical processing of the foreign-accented words is as good as that of the native-produced words. Taken together, the overall recognition difficulty of foreign-accented stimuli, as well as the differentially increased processing difficulty for accented dense words (observed in Experiment 1), mainly stems from the lexical level, due to the increased lexical competition posed by the similar sounding word candidates

IberSPEECH 2020: XI Jornadas en Tecnología del Habla and VII Iberian SLTech

IberSPEECH2020 is a two-day event, bringing together the best researchers and practitioners in speech and language technologies in Iberian languages to promote interaction and discussion. The organizing committee has planned a wide variety of scientific and social activities, including technical paper presentations, keynote lectures, presentation of projects, laboratories activities, recent PhD thesis, discussion panels, a round table, and awards to the best thesis and papers. The program of IberSPEECH2020 includes a total of 32 contributions that will be presented distributed among 5 oral sessions, a PhD session, and a projects session. To ensure the quality of all the contributions, each submitted paper was reviewed by three members of the scientific review committee. All the papers in the conference will be accessible through the International Speech Communication Association (ISCA) Online Archive. Paper selection was based on the scores and comments provided by the scientific review committee, which includes 73 researchers from different institutions (mainly from Spain and Portugal, but also from France, Germany, Brazil, Iran, Greece, Hungary, Czech Republic, Ucrania, Slovenia). Furthermore, it is confirmed to publish an extension of selected papers as a special issue of the Journal of Applied Sciences, “IberSPEECH 2020: Speech and Language Technologies for Iberian Languages”, published by MDPI with fully open access. In addition to regular paper sessions, the IberSPEECH2020 scientific program features the following activities: the ALBAYZIN evaluation challenge session.Red Española de Tecnologías del Habla. Universidad de Valladoli

Essential Speech and Language Technology for Dutch: Results by the STEVIN-programme

Computational Linguistics; Germanic Languages; Artificial Intelligence (incl. Robotics); Computing Methodologie

A study on reusing resources of speech synthesis for closely-related languages

This thesis describes research on building a text-to-speech (TTS) framework that can accommodate the lack of linguistic information of under-resource languages by using existing resources from another language. It describes the adaptation process required when such limited resource is used. The main natural languages involved in this research are Malay and Iban language. The thesis includes a study on grapheme to phoneme mapping and the substitution of phonemes. A set of substitution matrices is presented which show the phoneme confusion in term of perception among respondents. The experiments conducted study the intelligibility as well as perception based on context of utterances. The study on the phonetic prosody is then presented and compared to the Klatt duration model. This is to find the similarities of cross language duration model if one exists. Then a comparative study of Iban native speaker with an Iban polyglot TTS using Malay resources is presented. This is to confirm that the prosody of Malay can be used to generate Iban synthesised speech. The central hypothesis of this thesis is that by using a closely-related language resource, a natural sounding speech can be produced. The aim of this research was to show that by sticking to the indigenous language characteristics, it is possible to build a polyglot synthesised speech system even with insufficient speech resources

Proceedings of the VIIth GSCP International Conference

The 7th International Conference of the Gruppo di Studi sulla Comunicazione Parlata, dedicated to the memory of Claire Blanche-Benveniste, chose as its main theme Speech and Corpora. The wide international origin of the 235 authors from 21 countries and 95 institutions led to papers on many different languages. The 89 papers of this volume reflect the themes of the conference: spoken corpora compilation and annotation, with the technological connected fields; the relation between prosody and pragmatics; speech pathologies; and different papers on phonetics, speech and linguistic analysis, pragmatics and sociolinguistics. Many papers are also dedicated to speech and second language studies. The online publication with FUP allows direct access to sound and video linked to papers (when downloaded)