The utilize of YouTube for teaching and learning English in this era is needed toimplement. This research aims to investigated Channel: Pronunciation withEmma able enhance students’ pronunciation at SMK Bina Mandiri Bekasi. designof Classroom Action Research (CAR) uses a quantitative descriptivemethod. Participants were 36 students from XI TKJ F MandiriBekasi. result showed that using Channel:P...

Pronunciation dictionaries are the interface between orthographic and phonetic representation of the speech signal and are thereby a substantial component of speech recognition systems. In many systems simple canonical pronunciation forms are used within the dictionary. They represent the “correct” pronunciation as they are found in lexicons and neither contain the most frequent pronunciation n...

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...

The performance of automatic speech recognition systems varies widely across different contexts. Very good performance can be achieved on single-speaker, large-vocabulary dictation in a clean acoustic environment, as well as on very small vocabulary tasks with much fewer constraints on the speakers and acoustic conditions. In other domains, speech recognition is still far from usable for real-w...

The performance of automatic speech recognition systems varies widely across different contexts. Very good performance can be achieved on single-speaker, large-vocabulary dictation in a clean acoustic environment, as well as on very small vocabulary tasks with much fewer constraints on the speakers and acoustic conditions. In other domains, speech recognition is still far from usable for real-w...

Modelling of pronunciation variability is an important part of the acoustic model of a speech recognition system. Good pronunciation models contribute to the robustness and portability of a speech recogniser. Usually pronunciation modelling is associated with the recognition lexicon which allows a direct control of HMM selection. However, in state-of-the-art systems the use of clustering techni...

In this paper, methods for reconciling pronunciation differences between a rule-based front-end and the pronunciations observed in a database of recorded speech are presented. The methods are applied to the IBM Expressive Speech Synthesis System [1] for both unrestricted and limited-domain text-to-speech synthesis. One method is based on constructing a multiple pronunciation lattice for the giv...

We describe an algorithm to learn word pronunciations from acoustic data. The algorithm jointly optimizes the pronunciation of a word using (a) the acoustic match of this pronunciation to the observed data, and (b) how “linguistically reasonable” the pronunciation is. Variations of word pronunciations in the recognition dictionary (which was created by linguists), are used to train a model of w...

This study investigates whether a computer assisted pronunciation training (CAPT) system can help young learners improve word-level pronunciation skills in English as a foreign language at a level comparable to that achieved through traditional teacher-led training. The pronunciation improvement of a group of learners of 11 years of age receiving teacher-fronted instruction was compared to that...

Due to the large variability of pronunciation in spontaneous speech, pronunciation modeling becomes a more challenging and essential part in speech recognition. In this paper, we describe two different approaches of pronunciation modeling by using decision tree. At lexical level, a pronunciation variation dictionary is built to obtain alternative pronunciations for each word, in which each entr...