The purpose of the investigation was to compare mean voice onset time in young and old male subjects, as well as to examine variability of VOT productions with age for prevocalic bilabial, alveolar, and velar voiced and voiceless stop consonants. Forty-five Caucasion.males were divided equally into three.age groups. Ten tokens of six stimulus words were recorded and wide band spectrograms were made. Results of an analysis of variance revealed no significant differences in VOT with age when averages of the phonemes were used for analysis; however, a significant interaction between age and voiced phonemes was found when individual trials of phoneme productions were used for analysis.

The main focus of this dissertation is to investigate to what extent Japanese English-as-an-additional-language (EAL) learners have mastered default grapheme-phoneme correspondence (GPC) patterns of North American English vowels. The underlying motivation of this research comes from my observation that many mispronunciations of English vowels by Japanese EAL learners in formal learning settings are caused by their misinterpretation of English spellings rather than by phonological factors. Traditionally, Japanese speakers’ mispronunciations of English vowels have been attributed to a phonological factor that there is a mismatch of vowel inventories between English and Japanese. However, Nogita and Lin (2016) found that when vowel length and diphthongization are taken into consideration, native Japanese speakers are able to produce all the 13 North American English vowels although not necessarily in a native-like manner. This seems to suggest that other factors than the vowel inventory difference are responsible for the Japanese speakers EAL pronunciation errors. One such factor can be that Japanese EAL learners have not grasped the English GPC patterns and their misinterpretation of the spellings causes their pronunciation errors. To see if a GPC problem really plays a role, this dissertation examines how Japanese EAL learners map all the 13 North American English vowels with English vowel graphemes. In order to examine Japanese EAL learners’ knowledge of English vowel GPC, I conducted both reading and spelling tasks with English-like one-syllable nonsense words. In the reading task (e.g., reading aloud <snad>, <staw>, <stoe>, <nube>, etc.), the results showed that the Japanese EAL participants read vowel letters differently from native English speaking participants 40.1% of the time. In the spelling task (e.g., listening and spelling out native utterances of such syllables as [sneɪ], [zɑ:d], [gaʊ], [fʌd], etc.), the results showed that the Japanese EAL participants spelled out vowel sounds differently from native English speaking participants 60.0% of the time. These results suggest that the Japanese EAL participants’ English vowel grapheme-phoneme mapping patterns were quite different from those of the native English-speaking participants. In more details, the results showed that some correspondences were performed very well in both grapheme-to-phoneme and phoneme-to-grapheme directions presumably because of the similarities between the English GPC and the standardized Japanese romanization GPC: specifically, <e>-[ɛ] (in a closed syllable) and <oi, oy>-[ɔɪ]. In contrast, some correspondences were performed very poorly in both directions presumably in part because of the differences between the English GPC and the standardized Japanese romanization: specifically, <aw, au>-[ɑ:], <ow, ou>-[aʊ], <uh#>-[ʌ#] (# = word-final), <i>-[ɪ], and to a lesser extent <o>-[ɑ:] (in a closed syllable), and <o#, oe#, oh#>-[oʊ]. There were also correspondences that were performed very well only in the grapheme-to-phoneme direction but not in the other direction: specifically, word-medial <ee>-to-[i:] and <a_e>-to-[eɪ]. To a lesser extent, the <u>-to-[ʌ] conversion was also much less problematic than the [ʌ]-to-<u> conversion, although the <u>-[ʌ] correspondence was performed relatively poorly overall. Finally, none of the correspondences were performed very well only in the phoneme-to-grapheme direction but not in the other direction, but there were correspondences that showed this tendency. For example, the [æ: (æə)]-to-<a> conversion was much less problematic than the <a>-to-[æ: (æə)] conversion. Pedagogically, these results seem to suggest that Japanese EAL learners can benefit from being taught English default GPC patterns in order for them to improve on their graphophonic skills. / Graduate / 2017-08-23 / 0290 / 0279 / akitsugu@uvic.ca

Esta dissertação de mestrado apresenta um banco de figuras e palavras. O banco objetiva servir para a aumentar a validade e precisão dos instrumentos de avaliação, bem como a eficácia dos materiais instrucionais para desenvolvimento de linguagem. Este banco contém 971 entradas lexicais. Cada entrada contém uma figura e seu correspondente nome escrito. A figura é analisada em termos de grau de univocidade (grau de concordância na nomeação). O nome da figura é analisado separadamente em três formas: palavra escrita visível, palavra falada audível, e palavra falada visível (lida orofacialmente). Palavras escritas visíveis são compostas de grafemas. São analisadas em termos de seu grau de familiaridade e reconhecibilidade (grau em que pode ser lida via rota lexical) e decodificabilidade (grau em que pode ser lida pela rota perilexical ou fonológica). Palavras ouvidas audíveis são compostas de fonemas. São analisadas em termos do grau de cifrabilidade (grau de facilidade com que podem ser escritas via rota perilexical). Palavras faladas vistas são compostas de fanerolaliemas. São analisadas em termos do grau de legibilidade orofacial (grau em que podem ser compreendidas apenas pela visão), audibilizabilidade (grau em que a imagem auditiva dos fonemas pode ser evocada por fanerolaliemas durante a leitura orofacial visual), e cifrabilidade (grau de facilidade com que podem ser escritas via rota perilexical). O banco é composto de 971 entradas lexicais, cada qual composta de uma figura (à esquerda) e de vários dados pertinentes ao seu nome correspondente (à direita). O lado direito da entrada é composto de seis campos. O Campo 1 fornece o o nome da figura escrito em dois alfabetos: alfabeto romano e alfabeto fonético internacional. Ele também fornece a categoria semântica à qual pertence a palavra. O Campo 2 fornece o número da figura (para indexar todas as 971 figuras do banco). O Campo 3 fornece a univocidade da figura numa escala de 0-100 pontos separadamente para crianças de 2, 3, 4, 5, 6 7-10 anos de idade, bem como para adultos. O Campo 4 fornece a palavra escrita visível tal como analisada em termos de seu grau de familiaridade ou reconhecibilidade (grau em que pode ser lida via rota lexical) numa escala de 1-9 pontos, separadamente para crianças de 5º ano, 4º ano, 3º ano, 2º ano, e 1º ano. Nessa escala, 5 corresponde à média, 6 a 1 erro-padrão (EP) acima da média, 7 a 2 EP acima da média e assim por diante até 9; ao passo que 4 corresponde 1 EP abaixo da média, 3 a 2 EP abaixo da média, e assim por diante até 1. O Campo 5 é composto de quatro linhas, cada qual dividida em quatro colunas. A Linha 1 fornece o grau de decifrabilidade (grau com que pode ser lida pela rota perilexical) da palavra escrita visível, numa escala de 0-1. A Linha 2 fornece o grau de cifrabilidade da palavra ouvida (grau com que pode ser escrita pela rota perilexical), numa escala de 0-1. A Linha 3 fornece o grau de audibilizabilidade da palavra falada lida orofacialmente (grau com que sequência de fanerolaliemas pode ser convertida em sequência de fonemas), numa escala de 0-1. A Linha 3 fornece o grau de cifrabilidade da palavra falada lida orofacialmente (grau com que sequência de fanerolaliemas pode ser convertida em sequência de grafemas), numa escala de 0-1. Cada palavra é dividida em suas colunas. cada coluna fornece os dados referentes à linha em questão em uma de quatro formas diferentes. Nas Colunas 1 e 2, dados consistem na média das razões independente da incidência. Nas Colunas 3 e 4, dados consistem na média das razões ponderada por incidência diferencial. Nas Colunas 1 e 3 os dados consistem na média das razões independentemente da tonicidade da fala (seja ouvida ou vista) na pronúncia. Nas Colunas 2 e 4, os dados consistem na média das razões ponderada pela tonicidade diferencial da fala (seja ouvida ou vista) na pronúncia. Por exemplo, a Linha 1 fornece o grau de decifrabilidade grafema-fonema da palavra escrita visível. Na Coluna 1 decoficabilidade é calculada como mera média de razões independente da incidência ou tonicidade. Na Coluna 2 decodificabilidade é calculada como média das razões independente da incidência mas ponderasa pela tonicidade. Na Coluna 3 decodificabilidade é calculada como média de razões ponderadas em termos de incidência mas independente de tonicidade. Na Coluna 4 decodificabilidade é calculada como média de razões ponderadas em termos de incidência e de tonicidade. O Campo 6 fornece o grau de legibilidade orofacial da fala vista, numa escala de 0-1. O grau de legibilidade orofacial é apresentado em quatro formas. Nas Colunas 1 e 2 ela se encontra calculada segundo o modelo Dória; nas Colunas 3 e 4 ela se encontra calculada segundo o modelo Fonético-Articulatório. Nas Colunas 1 e 3 ela é calculada independentemente da tonicidade da pronúncia; nas Colunas 2 e 4 ela é calculada de modo ponderado pela tonicidade diferencial da pronúncia / This master\'s thesis presents a new sourcebook aimed at increasing the validity and precision of language assessment tools, as well as the efficacy of instructional materials for language development. The sourcebook contains 971 lexical entries. Each entry contains a picture and its corresponding written name. The picture is analyzed in terms of its degree of univocity (i.e., picture naming agreement). The picture name is analyzed separately in three forms: visual written word, auditory spoken word, and visual spoken word (i.e., speechreading). Visual written word is made of graphemes. It is analyzed in terms of its degree of both: familiarity or recognizability (i.e., the degree to which it is suitable to be read via lexical reading route) and decodibility (i.e., the degree to which it is suitable to be read via perilexical reading route). Auditory spoken word is made of phonemes. It is analyzed in terms of its degree of encodibility (i.e., the degree to which it may be suitable for writing or spelling via perilexical spelling route). Visual spoken word is made of visemes. It is analyzed in terms of its degree of: speechreadability (i.e., the degree to which it may be understood via visual speechreading), audibilizability (i.e., the degree to which the auditory imagery of phonemes can be evoked by mouthshapes or visemes during speechreading), and encodibility (i.e., the degree to which it is suitable to be written or spelled correctly via perilexical route). The sourcebook is made of 971 lexical entries. Each entry is made of a picture (on the left) and several data pertaining to its corresponding name (on the right). The right side of the entry is made of six areas. The first area provides the picture name as it is written in both alphabets: the Roman alphabet (orthographic form) and the International Phonetic Alphabet. It also provides the semantic category to which the word belongs. The second area provides the picture number (for indexing all the 971 pictures of the sourcebook). The third area provides the picture univocity in a 0-100 scale for children aged: 2 years, 3 years, 4 years, 5 years, 6 years, 7 to 10 years, as well as for adults. The fourth area provides the visual written word as it is analyzed in terms of its degree of familiarity or recognizability (i.e., the degree to which the written word is suitable to be read via lexical reading route) in a 1-9 point scale, for children from 5th grade, 4th grade, 3rd grade, 2nd grade, and 1st grade. In such a scale, 5 corresponds to the mean, 6 is the mean plus 1 standard error, 7 is the mean plus 2 standard errors and so forth until 9, whereas 4 corresponds to the mean minus 1 standard error, 3 corresponds to the mean minus 2 standard errors and so forth until 1, which corresponds to the mean minus 4 standar erros. The fifth area is made of four lines. Each line is divided into four columns. The first line provides the visual written word degree of decodibility (i.e., the degree to which it is suitable to be read via perilexical reading route) in a 0-1 scale. The second line provides the auditory spoken word degree of encodibility (i.e., the degree to which it may be suitable for writing or spelling via perilexical spelling route) in a 0-1 scale. The third line provides the visual spoken word degree of audibilizability (i.e., the degree to which the auditory imagery of phonemes can be evoked by mouthshapes or visemes during speechreading) in a 0-1 scale. The fouth line provides the visual spoken word degree of encodibility (i.e., the degree to which it is suitable to be written or spelled correctly via perilexical route) in a 0-1 scale. Each line is divided into four columns. Each column presents the data pertaining to the line in question in 1 of 4 different forms. In the first and second columns the data consist of the mean of the ratios regardless of incidence. In the third and fourth columns the data consist of the mean of the ratios weighted by differencial incidence. In the first and third columns the data consist of the mean of the ratios regardless of tonicity of speech (either auditory or visual) in pronunciation. In the second and fourth columns the data consist of the mean of the ratios weighted by differencial tonicity of speech (either auditory or visual) in pronunciation. For instance the first line provides the visual written word degree of decodibility (i.e., grapheme to phoneme decoding). In the first column decodibility is calculated as a mere mean of the ratios regardless of either incidence or tonicity. In the second column decodibility is calculated as a mean of the ratios regardless of incidence but weighted in terms of tonicity. In the third column decodibility is calculated as a mean of the ratios weighted in terms of incidence but regardless of tonicity. In the fourth column it is calculated as a mean of the ratios weighted in terms of both incidence and tonicity. The sixth area provides the visual spoken word degree of speechreadability (i.e., the degree to which it may be understood via visual speechreading) in a 0-1 scale. The speechreadability is presented in 1 of 4 different forms. In the first and second columns, the speechreadability is calculated according to Doria\'s model. In the third and fourth columns it is calculated according to a phonetic model. In the first column and third columns it is calculated regardless of tonicity in pronunciation. In the second and fourth columns it is calculated in a way that is weighted by the differencial tonicity in pronunciation

Esta dissertação de mestrado apresenta um banco de figuras e palavras. O banco objetiva servir para a aumentar a validade e precisão dos instrumentos de avaliação, bem como a eficácia dos materiais instrucionais para desenvolvimento de linguagem. Este banco contém 971 entradas lexicais. Cada entrada contém uma figura e seu correspondente nome escrito. A figura é analisada em termos de grau de univocidade (grau de concordância na nomeação). O nome da figura é analisado separadamente em três formas: palavra escrita visível, palavra falada audível, e palavra falada visível (lida orofacialmente). Palavras escritas visíveis são compostas de grafemas. São analisadas em termos de seu grau de familiaridade e reconhecibilidade (grau em que pode ser lida via rota lexical) e decodificabilidade (grau em que pode ser lida pela rota perilexical ou fonológica). Palavras ouvidas audíveis são compostas de fonemas. São analisadas em termos do grau de cifrabilidade (grau de facilidade com que podem ser escritas via rota perilexical). Palavras faladas vistas são compostas de fanerolaliemas. São analisadas em termos do grau de legibilidade orofacial (grau em que podem ser compreendidas apenas pela visão), audibilizabilidade (grau em que a imagem auditiva dos fonemas pode ser evocada por fanerolaliemas durante a leitura orofacial visual), e cifrabilidade (grau de facilidade com que podem ser escritas via rota perilexical). O banco é composto de 971 entradas lexicais, cada qual composta de uma figura (à esquerda) e de vários dados pertinentes ao seu nome correspondente (à direita). O lado direito da entrada é composto de seis campos. O Campo 1 fornece o o nome da figura escrito em dois alfabetos: alfabeto romano e alfabeto fonético internacional. Ele também fornece a categoria semântica à qual pertence a palavra. O Campo 2 fornece o número da figura (para indexar todas as 971 figuras do banco). O Campo 3 fornece a univocidade da figura numa escala de 0-100 pontos separadamente para crianças de 2, 3, 4, 5, 6 7-10 anos de idade, bem como para adultos. O Campo 4 fornece a palavra escrita visível tal como analisada em termos de seu grau de familiaridade ou reconhecibilidade (grau em que pode ser lida via rota lexical) numa escala de 1-9 pontos, separadamente para crianças de 5º ano, 4º ano, 3º ano, 2º ano, e 1º ano. Nessa escala, 5 corresponde à média, 6 a 1 erro-padrão (EP) acima da média, 7 a 2 EP acima da média e assim por diante até 9; ao passo que 4 corresponde 1 EP abaixo da média, 3 a 2 EP abaixo da média, e assim por diante até 1. O Campo 5 é composto de quatro linhas, cada qual dividida em quatro colunas. A Linha 1 fornece o grau de decifrabilidade (grau com que pode ser lida pela rota perilexical) da palavra escrita visível, numa escala de 0-1. A Linha 2 fornece o grau de cifrabilidade da palavra ouvida (grau com que pode ser escrita pela rota perilexical), numa escala de 0-1. A Linha 3 fornece o grau de audibilizabilidade da palavra falada lida orofacialmente (grau com que sequência de fanerolaliemas pode ser convertida em sequência de fonemas), numa escala de 0-1. A Linha 3 fornece o grau de cifrabilidade da palavra falada lida orofacialmente (grau com que sequência de fanerolaliemas pode ser convertida em sequência de grafemas), numa escala de 0-1. Cada palavra é dividida em suas colunas. cada coluna fornece os dados referentes à linha em questão em uma de quatro formas diferentes. Nas Colunas 1 e 2, dados consistem na média das razões independente da incidência. Nas Colunas 3 e 4, dados consistem na média das razões ponderada por incidência diferencial. Nas Colunas 1 e 3 os dados consistem na média das razões independentemente da tonicidade da fala (seja ouvida ou vista) na pronúncia. Nas Colunas 2 e 4, os dados consistem na média das razões ponderada pela tonicidade diferencial da fala (seja ouvida ou vista) na pronúncia. Por exemplo, a Linha 1 fornece o grau de decifrabilidade grafema-fonema da palavra escrita visível. Na Coluna 1 decoficabilidade é calculada como mera média de razões independente da incidência ou tonicidade. Na Coluna 2 decodificabilidade é calculada como média das razões independente da incidência mas ponderasa pela tonicidade. Na Coluna 3 decodificabilidade é calculada como média de razões ponderadas em termos de incidência mas independente de tonicidade. Na Coluna 4 decodificabilidade é calculada como média de razões ponderadas em termos de incidência e de tonicidade. O Campo 6 fornece o grau de legibilidade orofacial da fala vista, numa escala de 0-1. O grau de legibilidade orofacial é apresentado em quatro formas. Nas Colunas 1 e 2 ela se encontra calculada segundo o modelo Dória; nas Colunas 3 e 4 ela se encontra calculada segundo o modelo Fonético-Articulatório. Nas Colunas 1 e 3 ela é calculada independentemente da tonicidade da pronúncia; nas Colunas 2 e 4 ela é calculada de modo ponderado pela tonicidade diferencial da pronúncia / This master\'s thesis presents a new sourcebook aimed at increasing the validity and precision of language assessment tools, as well as the efficacy of instructional materials for language development. The sourcebook contains 971 lexical entries. Each entry contains a picture and its corresponding written name. The picture is analyzed in terms of its degree of univocity (i.e., picture naming agreement). The picture name is analyzed separately in three forms: visual written word, auditory spoken word, and visual spoken word (i.e., speechreading). Visual written word is made of graphemes. It is analyzed in terms of its degree of both: familiarity or recognizability (i.e., the degree to which it is suitable to be read via lexical reading route) and decodibility (i.e., the degree to which it is suitable to be read via perilexical reading route). Auditory spoken word is made of phonemes. It is analyzed in terms of its degree of encodibility (i.e., the degree to which it may be suitable for writing or spelling via perilexical spelling route). Visual spoken word is made of visemes. It is analyzed in terms of its degree of: speechreadability (i.e., the degree to which it may be understood via visual speechreading), audibilizability (i.e., the degree to which the auditory imagery of phonemes can be evoked by mouthshapes or visemes during speechreading), and encodibility (i.e., the degree to which it is suitable to be written or spelled correctly via perilexical route). The sourcebook is made of 971 lexical entries. Each entry is made of a picture (on the left) and several data pertaining to its corresponding name (on the right). The right side of the entry is made of six areas. The first area provides the picture name as it is written in both alphabets: the Roman alphabet (orthographic form) and the International Phonetic Alphabet. It also provides the semantic category to which the word belongs. The second area provides the picture number (for indexing all the 971 pictures of the sourcebook). The third area provides the picture univocity in a 0-100 scale for children aged: 2 years, 3 years, 4 years, 5 years, 6 years, 7 to 10 years, as well as for adults. The fourth area provides the visual written word as it is analyzed in terms of its degree of familiarity or recognizability (i.e., the degree to which the written word is suitable to be read via lexical reading route) in a 1-9 point scale, for children from 5th grade, 4th grade, 3rd grade, 2nd grade, and 1st grade. In such a scale, 5 corresponds to the mean, 6 is the mean plus 1 standard error, 7 is the mean plus 2 standard errors and so forth until 9, whereas 4 corresponds to the mean minus 1 standard error, 3 corresponds to the mean minus 2 standard errors and so forth until 1, which corresponds to the mean minus 4 standar erros. The fifth area is made of four lines. Each line is divided into four columns. The first line provides the visual written word degree of decodibility (i.e., the degree to which it is suitable to be read via perilexical reading route) in a 0-1 scale. The second line provides the auditory spoken word degree of encodibility (i.e., the degree to which it may be suitable for writing or spelling via perilexical spelling route) in a 0-1 scale. The third line provides the visual spoken word degree of audibilizability (i.e., the degree to which the auditory imagery of phonemes can be evoked by mouthshapes or visemes during speechreading) in a 0-1 scale. The fouth line provides the visual spoken word degree of encodibility (i.e., the degree to which it is suitable to be written or spelled correctly via perilexical route) in a 0-1 scale. Each line is divided into four columns. Each column presents the data pertaining to the line in question in 1 of 4 different forms. In the first and second columns the data consist of the mean of the ratios regardless of incidence. In the third and fourth columns the data consist of the mean of the ratios weighted by differencial incidence. In the first and third columns the data consist of the mean of the ratios regardless of tonicity of speech (either auditory or visual) in pronunciation. In the second and fourth columns the data consist of the mean of the ratios weighted by differencial tonicity of speech (either auditory or visual) in pronunciation. For instance the first line provides the visual written word degree of decodibility (i.e., grapheme to phoneme decoding). In the first column decodibility is calculated as a mere mean of the ratios regardless of either incidence or tonicity. In the second column decodibility is calculated as a mean of the ratios regardless of incidence but weighted in terms of tonicity. In the third column decodibility is calculated as a mean of the ratios weighted in terms of incidence but regardless of tonicity. In the fourth column it is calculated as a mean of the ratios weighted in terms of both incidence and tonicity. The sixth area provides the visual spoken word degree of speechreadability (i.e., the degree to which it may be understood via visual speechreading) in a 0-1 scale. The speechreadability is presented in 1 of 4 different forms. In the first and second columns, the speechreadability is calculated according to Doria\'s model. In the third and fourth columns it is calculated according to a phonetic model. In the first column and third columns it is calculated regardless of tonicity in pronunciation. In the second and fourth columns it is calculated in a way that is weighted by the differencial tonicity in pronunciation

The present study describes the results of a 2 week perturbation experiment where speaker's vocal tract shape was modified due to the presence of an artificial palate. The aim of the work is to investigate whether speakers adapt towards acoustic or articulatory targets. Speakers were recorded regularly over the adaptation time via electromagnetic articulography and acoustics. Immediately after perturbation onset speaker's auditory feedback was masked with white noise in order to investigate speakers' compensatory behavior when auditory feedback was absent.<br />The results of acoustic measurements show that in vowel production speakers compensate very soon. The compensation in fricatives takes longer and is in some cases not completed within the two weeks. Within a session and for each speaker the sounds can be distinguished solely by acoustic parameters. The differences between the session when no auditory feedback was available and the session when auditory feedback was available was greater for vowels with les palatal contact than for vowel with much palatal contact. In consonant production auditory feedback is primarily used in order to adapt sibilant productions. In general, adaptation tries to keep or enlarge the articulatory and acoustic space between the sounds. Over sessions speakers show motor equivalent strategies (lip protrusion vs. tongue back raising) in the production of /u/. Measurements of tangential jerk suggest that after perturbation onset there is an increase in articulatory effort which is followed by a decrease towards the end of the adaptation time.<br />The compensatory abilities of speakers when no auditory feedback is available suggest that speakers dispose of an articulatory representation. The fact that motor equivalent strategies are used by the speakers, however, supports acoustic representations of speech. It is therefore concluded that articulatory representations belong to the speech production tasks. However since they are modified as soon as the acoustic output is not the desired one any more, they rather function in the domain of movement organization and the acoustic representations dominate.

<p>A text-to-speech system is a complex system consisting of several different modules such as grapheme-to-phoneme conversion, articulatory and prosodic modelling, voice modelling etc.</p><p>This dissertation is aimed at the creation of the initial part of a text-to-speech system, i.e. the grapheme-to-phoneme conversion, designed for Swedish. The problem area at hand is the conversion of orthographic text into a phonetic representation that can be used as a basis for a future complete text-to speech system.</p><p>The central issue of the dissertation is the grapheme-to-phoneme conversion and the elaboration of rules and algorithms required to achieve this task. The dissertation aims to prove that it is possible to make such a conversion by a rule-based algorithm with reasonable performance. Another goal is to find a way to represent phonotactic rules in a form suitable for parsing. It also aims to find and analyze problematic structures in written text compared to phonetic realization.</p><p>This work proposes a knowledge-based grapheme-to-phoneme conversion system for Swedish. The system suggested here is implemented, tested, evaluated and compared to other existing systems. The results achieved are promising, and show that the system is fast, with a high degree of accuracy.</p>

Στα πλάισια της ανάλυσης ομιλίας, η παρούσα διατριβή παρουσιάζει έναν εύρωστο Αναγνωριστή Φωνημάτων ανεξαρτήτου Γλώσσας για τις ανάγκες της Αυτόματης Αναγνώρισης Γλώσσας. Η υλοποίηση του Συστήματος βασίζεται στους MFCC συντλεστές οι οποίοι αποτελούν τους χαρακτηριστικούς περιγραφείς ομιλίας, στη διαδικασία διανυσματικής κβαντοποίησης κατά την οποία δημιουργούνται τα κωδικά βιβλία εκπαίδευσης του Συστήματος και στα πιθανοτικά νευρωνικά δίκτυα (Propabilistic Neural Networks) για την εκπαίδευση του Συστήματος και την αναγνώριση των άγνωστων φωνημάτων. / In our thesis we present a language-independent phoneme recognizer for the needs of Automatic Language Identification. The system is based on: 1. the MFCCs for acoustic-spectral representation of phonemes, 2. vector quantization for creating the training codebooks of the system and 3. the Propabilistic Neural Networks (PNNs) for the training of the system and the classification of unknown phonemes.

Kalbos animacija plačiai naudojama technikos įrenginiuose siekiant kurtiesiems, vaikams, vidutinio ir vyresnio amžiaus žmonėms sudaryti vienodas bendravimo galimybes. Žmonės yra labai jautrūs veido išvaizdos pokyčiams, todėl kalbos animavimas yra sudėtingas procesas, kurio metu žmogaus kalboje atpažinta akustinė informacija (fonemos) yra vizualizuojama naudojant specialiai sumodeliuotas veido išraiškas vadinamas vizemomis. Didžiausią įtaką kalbos animacijos tikroviškumui turi teisingas fonemas atitinkančių vizemų identifikavimas, modeliavimas ir jų išrikiavimas laiko juostoje. Tačiau, norint užtikrinti kalbos animacijos natūralumą, būtina papildomai išnalizuoti vizemų įtaką kaimyninėms fonemoms ir atsižvelgiant į animuojamos kalbos fonetines savybes sukurti koartikuliacijos valdymo modelį. Kiekvienos kalbos fonetika skiriasi, todėl kitai vienai kalbai sukurta animavimo sistema nėra tiesiogiai tinkama kitai kalbai animuoti. Kalbos animavimo karkasas, kuriame realizuojama Lietuvių kalbai skirta animavimo technologija, turi būti sukurta lietuvių kalbai vizualizuoti. Darbą sudaro įvadas, trys pagrindiniai skyriai, bendrosios išvados, literatūros sąrašas, publikacijų sąrašas. Pirmame skyriuje Skyriuje analizuojamos pasaulyje naudojamos kalbos animavimo technologijos. Kalbos signalas yra ir girdimas, ir matomas, todėl jos animacija yra sudėtinis procesas priklausantis nuo pasirinktos veido modeliavimo metodikos, kalbos signalo tipo, ir koartikuliacijos valdymo modelio. Antrajame... [toliau žr. visą tekstą] / Speech animation is widely used in technical devices to allow the growing number of hearing impaired persons, children, middle-aged and elderly equal participation in communication. Speech animation systems (“Talking heads”) are basically driven by speech phonetics and their visual representation – visemes. Acuraccy of the chosen speech recognition engine, naturally looking visemes, phoneme to viseme mapping and coarticulation control model considerably influence the quality of animated speech. Speech animation is strongly related with language phonetics, so new“Talking heads” should be created to animate different languages. Framework suitable to animate Lithuanian speech, which includes two new models that help to improve intelligibility of animated Lithuanian speech is used to create Lithuanian „Talking head” „LIT”. The dissertation consists of Introduction, three main chapters and general conclusions. Chapter 1 provides the analysis of the existing speech animation technologies. Different facial modelling techniques are analysed to define the most suitable 3D „Talking head” modelling technique for Lithuanian language. Viseme classification experiments across different languages are analysed to identify variety of viseme classification methods. Coarticulation control models are compared to deside which one should be used to define coarticulation of Lithuanian speech. Chapter 2 describes theoretical framework for Lithuanian speech animation. Translingual visual speech... [to full text]

Grapheme-based speech recognition systems are faster to develop, but typically do not reach the same level of performance as phoneme-based systems. Using Afrikaans speech recognition as a case study, we first analyse the reasons for the discrepancy in performance, before introducing a technique for improving the performance of standard grapheme-based systems. It is found that by handling a relatively small number of irregular words through phoneme-to-grapheme (P2G) transliteration – transforming the original orthography of irregular words to an ‘idealised’ orthography – grapheme-based accuracy can be improved. An analysis of speech recognition accuracy based on word categories shows that P2G transliteration succeeds in improving certain word categories in which grapheme-based systems typically perform poorly, and that the problematic categories can be identified prior to system development. An evaluation is offered of when category-based P2G transliteration is beneficial and methods to implement the technique in practice are discussed. Comparative results are obtained for a second language (Vietnamese) in order to determine whether the technique can be generalised. / MSc (Computer Science) North-West University, Vaal Triangle Campus, 2014

The aim of this thesis was to better understand English as second language Nigerian children’s reading comprehension attainment, the first such study to be conducted in Nigeria. In the thesis three studies were conducted to investigate the influence of cognitive and decoding/reading skills on the children’s reading comprehension attainment, namely the preliminary study (Chapter-3) with one primary school in Nigeria, the main study (Chapter-4) with 13 state-run primary schools, and the control study (Chapter-5) including four primary schools in London, respectively. It was found that English as second language children’s reading comprehension performance is significantly influenced by cognitive, decoding and chronological age. The development of cognitive skills which is necessary for success in reading comprehension development is also dependent upon chronological age. That is, age-related increase in cognitive skills brings about increased engagement and more efficient reading comprehension attainment in the children. The normal cognitive development of the children had a positive role also on the children’s performance on language tests necessary for text comprehension. The study found that school socioeconomic background played a significant impact in the performance of Nigerian English as second language children – the better the socioeconomic background of the school the higher the reading comprehension attainment of the children. Furthermore gender was not a factor in the performance and development of reading comprehension by English as Second Language Nigerian children. This implies that parents, teachers and schools motivate and support children irrespective of being boys or girls to realise their full potentials without any discrimination. Having reviewed few theories of reading acquisition/development, the Simple view of reading (SVR) was found to be more appropriate for adoption in this study of Nigerian English as second language children’s reading comprehension attainment. The theory postulates that text comprehension is achieved when children have decoding skills and linguistic comprehension knowledge. The results obtained in Chapters 3 and 4 were in line with the Simple view of reading’s assertion – text comprehension depends on decoding and cognitive skills.