Abstract: Accent identification has grown over the past decade. There has been decent success when a priori knowledge about the accents is available.

We build on the GMM approach by exploring the ef- fects of applying ensemble learning. Ensemble learning im- proves upon classifiers at the expense of ...

Recently, Gaussian Mixture Models (GMMs) have been used as an unsupervised alternative to these phoneme-based models, but they have had limited success unless ...

Accent identification has grown over the past decade. There has been decent success when a priori knowledge about the accents is available.

... Learning American English Accents Using Ensemble Learning with GMMs | Accent identification has grown over the past decade. There has been decent success ...

Aug 30, 2024 · The MKELM model utilizes a novel weighted scheme to classify various non-native English accents, including Arabic, Chinese, Korean, French, and Spanish.

Learning American English Accents Using Ensemble Learning with GMMs · Computer Science, Linguistics. International Conference on Machine Learning and… · 2009.

... Learning Using Sphere Factor Analysis ... American English Accents Using Ensemble Learning with GMMs ... Classifier ...

In this paper, we apply Gaussian Mixture Models (GMM) and Deep Neural Network (DNN) to identify the speaker accent in reverberant environments. The combination ...

Jul 20, 2021 · In this work, the labeling of primary accents uses a labeling algorithm that combines morphological rules and machine learning.