8,392 research outputs found

    Language identification with suprasegmental cues: A study based on speech resynthesis

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    This paper proposes a new experimental paradigm to explore the discriminability of languages, a question which is crucial to the child born in a bilingual environment. This paradigm employs the speech resynthesis technique, enabling the experimenter to preserve or degrade acoustic cues such as phonotactics, syllabic rhythm or intonation from natural utterances. English and Japanese sentences were resynthesized, preserving broad phonotactics, rhythm and intonation (Condition 1), rhythm and intonation (Condition 2), intonation only (Condition 3), or rhythm only (Condition 4). The findings support the notion that syllabic rhythm is a necessary and sufficient cue for French adult subjects to discriminate English from Japanese sentences. The results are consistent with previous research using low-pass filtered speech, as well as with phonological theories predicting rhythmic differences between languages. Thus, the new methodology proposed appears to be well-suited to study language discrimination. Applications for other domains of psycholinguistic research and for automatic language identification are considered

    Language Identification Using Visual Features

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    Automatic visual language identification (VLID) is the technology of using information derived from the visual appearance and movement of the speech articulators to iden- tify the language being spoken, without the use of any audio information. This technique for language identification (LID) is useful in situations in which conventional audio processing is ineffective (very noisy environments), or impossible (no audio signal is available). Research in this field is also beneficial in the related field of automatic lip-reading. This paper introduces several methods for visual language identification (VLID). They are based upon audio LID techniques, which exploit language phonology and phonotactics to discriminate languages. We show that VLID is possible in a speaker-dependent mode by discrimi- nating different languages spoken by an individual, and we then extend the technique to speaker-independent operation, taking pains to ensure that discrimination is not due to artefacts, either visual (e.g. skin-tone) or audio (e.g. rate of speaking). Although the low accuracy of visual speech recognition currently limits the performance of VLID, we can obtain an error-rate of < 10% in discriminating between Arabic and English on 19 speakers and using about 30s of visual speech

    Perception and production of English speech contrasts by bilingual children from Spanish-dominant backgrounds

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    Reading by six: how the best schools do it

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    PHONOTACTIC AND ACOUSTIC LANGUAGE RECOGNITION

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    Práce pojednává o fonotaktickém a akustickém přístupu pro automatické rozpoznávání jazyka. První část práce pojednává o fonotaktickém přístupu založeném na výskytu fonémových sekvenci v řeči. Nejdříve je prezentován popis vývoje fonémového rozpoznávače jako techniky pro přepis řeči do sekvence smysluplných symbolů. Hlavní důraz je kladen na dobré natrénování fonémového rozpoznávače a kombinaci výsledků z několika fonémových rozpoznávačů trénovaných na různých jazycích (Paralelní fonémové rozpoznávání následované jazykovými modely (PPRLM)). Práce také pojednává o nové technice anti-modely v PPRLM a studuje použití fonémových grafů místo nejlepšího přepisu. Na závěr práce jsou porovnány dva přístupy modelování výstupu fonémového rozpoznávače -- standardní n-gramové jazykové modely a binární rozhodovací stromy. Hlavní přínos v akustickém přístupu je diskriminativní modelování cílových modelů jazyků a první experimenty s kombinací diskriminativního trénování a na příznacích, kde byl odstraněn vliv kanálu. Práce dále zkoumá různé druhy technik fúzi akustického a fonotaktického přístupu. Všechny experimenty jsou provedeny na standardních datech z NIST evaluaci konané v letech 2003, 2005 a 2007, takže jsou přímo porovnatelné s výsledky ostatních skupin zabývajících se automatickým rozpoznáváním jazyka. S fúzí uvedených technik jsme posunuli state-of-the-art výsledky a dosáhli vynikajících výsledků ve dvou NIST evaluacích.This thesis deals with phonotactic and acoustic techniques for automatic language recognition (LRE). The first part of the thesis deals with the phonotactic language recognition based on co-occurrences of phone sequences in speech. A thorough study of phone recognition as tokenization technique for LRE is done, with focus on the amounts of training data for phone recognizer and on the combination of phone recognizers trained on several language (Parallel Phone Recognition followed by Language Model - PPRLM). The thesis also deals with novel technique of anti-models in PPRLM and investigates into using phone lattices instead of strings. The work on phonotactic approach is concluded by a comparison of classical n-gram modeling techniques and binary decision trees. The acoustic LRE was addressed too, with the main focus on discriminative techniques for training target language acoustic models and on initial (but successful) experiments with removing channel dependencies. We have also investigated into the fusion of phonotactic and acoustic approaches. All experiments were performed on standard data from NIST 2003, 2005 and 2007 evaluations so that the results are directly comparable to other laboratories in the LRE community. With the above mentioned techniques, the fused systems defined the state-of-the-art in the LRE field and reached excellent results in NIST evaluations.

    An acoustic-phonetic approach in automatic Arabic speech recognition

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    In a large vocabulary speech recognition system the broad phonetic classification technique is used instead of detailed phonetic analysis to overcome the variability in the acoustic realisation of utterances. The broad phonetic description of a word is used as a means of lexical access, where the lexicon is structured into sets of words sharing the same broad phonetic labelling. This approach has been applied to a large vocabulary isolated word Arabic speech recognition system. Statistical studies have been carried out on 10,000 Arabic words (converted to phonemic form) involving different combinations of broad phonetic classes. Some particular features of the Arabic language have been exploited. The results show that vowels represent about 43% of the total number of phonemes. They also show that about 38% of the words can uniquely be represented at this level by using eight broad phonetic classes. When introducing detailed vowel identification the percentage of uniquely specified words rises to 83%. These results suggest that a fully detailed phonetic analysis of the speech signal is perhaps unnecessary. In the adopted word recognition model, the consonants are classified into four broad phonetic classes, while the vowels are described by their phonemic form. A set of 100 words uttered by several speakers has been used to test the performance of the implemented approach. In the implemented recognition model, three procedures have been developed, namely voiced-unvoiced-silence segmentation, vowel detection and identification, and automatic spectral transition detection between phonemes within a word. The accuracy of both the V-UV-S and vowel recognition procedures is almost perfect. A broad phonetic segmentation procedure has been implemented, which exploits information from the above mentioned three procedures. Simple phonological constraints have been used to improve the accuracy of the segmentation process. The resultant sequence of labels are used for lexical access to retrieve the word or a small set of words sharing the same broad phonetic labelling. For the case of having more than one word-candidates, a verification procedure is used to choose the most likely one

    The acquisition of phonology and the classification of speech disorders in German-speaking children

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    PhD ThesisPhonological acquisition has been a major research topic for the past three decades. Several different theoretical concepts, accounting for the course of phonological acquisition, have emerged. While all these theories agree the need to explain language-specific differences during the course of development, they all also strongly argue for a universal pattern. This thesis aims to provide evidence for phonological theory in a cross-linguistic context by examining monolingual children acquiring German as their native language. A cross-sectional study of 177 normally developing children aged 1;6 to 5; 11 was found to generally support the concept of universality but also showed significant acquisition differences especially in comparison with English, a closely related language. It will be argued that to date only the concept of phonological saliency (So & Dodd, 1994; Zua Hua & Dodd, 2000) is able to fully explain language-specific findings. However, evidence for phonological theory cannot only be validated by using data from developmental cross-linguistic studies but also from data describing phonologically disordered children. The nature of the errors made and also the children's developmental history might provide information concerning the prerequisites for normal speech development and the cognitive processes involved in speech perception and production. ... This thesis will argue that developmental speech disorders of unknown origin follow a language-independent course that is constrained by a universal pattern. On the basis of normative data for any language investigated, it should be possible to detect universal subgroups of speech disorders across languages. The clinical implication of this conclusion is that therapy techniques can be applied cross-linguistically.Economic and Social Research Council
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