This paper describes the architecture and the implementation of a full-scale pronunciation lexicon for Turkish using finite state technology. The system produces at its output, a parallel representation of the pronunciation and the morphological analysis of the word form so that morphological disambiguation can be used to disambiguate pronunciation. The pronunciation representation is based on ...

in order to simplify the pronunciation ofthe adult's words,children use phonological processes inthe initial years oftheir speech growth.the present study aims at considering phonological processes ina group oftwo tofour-year old farsi speaking children.the results indicate that itisnot possible to correctly and precisely account forthe occurrences ofsuch processes in children’s pronunciat...

We propose a model-driven method for ensuring the quality of pronunciation dictionaries. The key ingredient is computing an alignment between letter strings and phoneme strings, a standard technique in pronunciation modeling. The novel aspect of our method is the use of informative, parametric alignment models which are refined iteratively as they are tested against the data. We discuss the use...

This paper presents the design and performance of a Malay grapheme to phoneme (G2P) tool for generating the pronunciation dictionary for a Malay automatic speech recognition system (ASR). The G2P tool is a rule based system. It is flexible in adding and removing rules, and handling of English words. The G2P tool also contains morphological and syllable tool, which it uses to determine the pronu...

In this paper, we propose speaker-dependent multiple-pronunciation lexical modeling for improving the performance of dysarthric automatic speech recognition (ASR). For each dysarthric speaker, a phoneme confusion matrix is first constructed from the results of phoneme recognition. Then, pronunciation variation rules are extracted by investigating the phoneme confusion matrix, and they are incor...

In this paper, a data-driven approach to statistical modeling pronunciation variation is proposed. It consists of learning stochastic pronunciation rules. The proposed method jointly models different rules that define the same transformation. Hierarchic Grouping Rule Inference (HIEGRI) algorithm is proposed to generate this model based on graphs. HIEGRI algorithm detects the common patterns of ...

In order to help understand why gains in pronunciation modeling have proven so elusive, we investigated which kinds of pronunciation variation are well captured by triphone models, and which are not. We do this by examining the change in behavior of a recognizer as it receives further triphone training. We show that many of the kinds of variation which previous pronunciation models attempt to c...

This paper describes the implementation of a full-scale pronunciation lexicon for Turkish using finite state technology. The system produces at its output, a parallel representation of the pronunciation and the morphological analysis of the word form so that morphological disambiguation can be used to disambiguate pronunciation. The pronunciation representation is based on the SAMPA standard an...

Modeling pronunciation variation is key for recognizing conversational speech. Previous efforts on pronunciation modeling by modifying dictionaries only yielded marginal improvement. Due to complex interaction between dictionaries and acoustic models, we believe a pronunciation modeling scheme is plausible only when closely coupled with the underlying acoustic model. This paper explores the use...

Articulatory information can support learning or remediating pronunciation of a second language (L2). This paper describes an electromagnetic articulometer-based visual-feedback approach using an articulatory target presented in real-time to facilitate L2 pronunciation learning. This approach trains learners to adjust articulatory positions to match targets for a L2 vowel estimated from product...