This study aims to investigate native speakers’ perception of prosodic variation of Japanese utterances. The pitch contour above the word level is hard to determine due to individual variation or pragmatic and para-linguistic factors. Nevertheless, native speakers’ intonation is relatively consistent as long as the context and intention of the utterance is predetermined. On the other hand, L2 s...

This article describes how the performance of a Dutch continuous speech recognizer was improved by modeling pronunciation variation. We propose a general procedure for modeling pronunciation variation. In short, it consists of adding pronunciation variants to the lexicon, retraining phone models and using language models to which the pronunciation variants have been added. First, within-word pr...

This article describes how the performance of a Dutch continuous speech recognizer was improved by modeling pronunciation variation. We propose a general procedure for modeling pronunciation variation. In short, it consists of adding pronunciation variants to the lexicon, retraining phone models and using language models to which the pronunciation variants have been added. First, within-word pr...

This paper addresses the problem of predicting the pronunciation of Japanese text. The difficulty of this task lies in the high degree of ambiguity in the pronunciation of Japanese characters and words. Previous approaches have either considered the task as a word-level classification problem based on a dictionary, which does not fare well in handling out-of-vocabulary (OOV) words; or solely fo...

This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilises a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native con®dence scores and on rejection statistics provided by human judges. Further improvemen...

Calculating posterior probability within a standard pronunciation space (SPS) is a common method in automatic pronunciation error detection (APED). However, to pronunciation errors outside the SPS, this kind of methods can only give an approximate solution, that may be not right in many applications. This paper expands the SPS to include more pronunciation errors, introduces a Bhattacharyya dis...

In the construction of whole-word acoustic models, we have previously demonstrated substantial gains by using MAP estimation to introduce a simple prior model of phonetic timing. Based solely on the word’s phonetic (dictionary) pronunciation, this simple model included no information about the individual durations of constituent phones. However, the problem of modeling segmental duration has lo...

In this work a number of novel techniques for improved treatment of spontaneous speech variabilities in large vocabulary automatic speech recognition are developed and evaluated on US English conversational speech and spontaneous medical dictations. Two main aspects of spontaneous speech modeling are addressed: The general handling of pronunciation variability and the individual and parallel tr...

This paper investigates whether individual speakers forming a homogeneous group differ in their choice and pronunciation of words when engaged in casual conversation, and if so, how they differ. More specifically, it examines whether the Balanced Winnow classifier is able to distinguish between the twenty speakers of the Ernestus Corpus of Spontaneous Dutch, who all have the same social backgro...

Introducing pronunciation models into decoding has been proven to be benefit to LVCSR. In this paper, a discriminative pronunciation modeling method is presented, within the framework of the Minimum Phone Error (MPE) training for HMM/GMM. In order to bring the pronunciation models into the MPE training, the auxiliary function is rewritten at word level and decomposes into two parts. One is for ...