Ariane Lazaridès

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Recently, we described a two-step self-learning approach for grapheme-to-phoneme (G2P) conversion [1]. In the first step, grapheme and phoneme strings in the training data are aligned via an iterative Viterbi procedure that may insert graphemic and phonemic nulls where required. In the second step, a Trie structure encoding pronunciation rules is generated.(More)
In the last few years, the power and simplicity of classification trees as acoustic modeling tools have gained them much popularity. In [1], we studied ‘‘tree units’’, which cluster parameters at the HMM level. Building on this earlier work, we examine some new variants of Young et al’s ‘‘tree states’’, which cluster parameters at the state level [2]. We(More)
This paper describes decision tree methodology and shows how it has been adapted to three diierent problems in speech recognition and understanding at CRIM and at FORWISS. The three problems are: 1. Development of context-dependent phone models (work carried out by CRIM researchers and partly inspired by FORWISS work on polyphones). Here, decision trees(More)
In this longitudinal study, we examined the moderating role of personality in the relationship between communication behaviors (withdrawal, dominance, criticism, support, and problem solving) and couple stability. At Time 1, 135 couples completed the NEO Five-Factor Inventory and the Dyadic Adjustment Scale. These couples were also videotaped during a(More)
In the last few years, the power and simplicity of classification trees as acoustic modeling tools have gained them much popularity. In [1], we studied ‘‘tree units’’, which cluster parameters at the HMM level. Building on this earlier work, we examine some new variants of Young et al’s ‘‘tree states’’, which cluster parameters at the state level [2]. We(More)
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