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The hidden Markov modelling experiments presented in this paper show that consonant identification results can be improved substantially if a neural network is used to extract linguistically relevant information from the acoustic signal before applying hidden Markov modelling. The neural network – or in this case a combination of two Kohonen networks –(More)
This paper describes three cross-language ASR experiments which use hidden Markov modelling. The first one shows that consonant identification improves when vowel transitions are used. In particular, the consonants' place of articulation is identified better, because the vowel transitions contain formant trajectories which depend on the consonant's place of(More)
In a production study, Bulgarian, English and German verses with regular poetic metrical metres of different types and elicited prose utterances with varied accentual patterns are produced in textual and iterative (dada) form and measured at syllable level according to the pairwise variability index (PVI) principle. Systematic differences in PVI values show(More)
This article presents preliminary results indicating that speakers have a different pitch range when they speak a foreign language compared to the pitch variation that occurs when they speak their native language. To this end, a learner corpus with French and German speakers was analyzed. Results suggest that speakers indeed produce a smaller pitch range in(More)
By mapping acoustic parameters onto phonetic features, it is possible to explicitly address the linguistic information in the signal. For the experiments presented in this paper, we mapped cepstral parameters onto two sets of phonetic features, one based on the IPA chart and the other on SPE. As a result, the phoneme identification rates in a hidden Markov(More)
1. Introduction It can be taken for granted that the first language (L1) influences the target language to be learned (L2) on all linguistic levels including the lexicon, morphosyntax, pragmatics and, most pertinent to the proposed corpus, sound structure and its phonetic implementation (e.g. Flege & Davidian 1984, Flege 1995). A typical example of L1-L2(More)
This study presents the results of a large-scale comparison of various measures of pitch range and pitch variation in two Slavic (Bulgarian and Polish) and two Germanic (German and British English) languages. The productions of twenty-two speakers per language (eleven male and eleven female) in two different tasks (read passages and number sets) are(More)
In this article we discuss implementation of some fundamental phonetic ideas related to what we shall call "relational processing" in a cross-language consonant identification system. The term relational processing refers to the way vowel transitions play a role in the identification of neighbouring consonants. Two experiments are described: first,(More)
This study investigates cross-language differences in pitch range and variation in four languages from two language groups: English and German (Germanic) and Bulgarian and Polish (Slavic). The analysis is based on large multi-speaker corpora (48 speakers for Polish, 60 for each of the other three languages). Linear mixed models were computed that include(More)
The acoustic-phonetic properties of words spoken with three different levels of accentuation (de-accented, pre-nuclear and nuclear accented in broad-focus and nuclear accented in narrow-focus) are examined in question-answer elicited sentences and iterative imitations (on the syllable da) produced by six French and six German speakers. Normalised parameter(More)