Bayesian Analysis of Phoneme Confusion Matrices
نویسندگان
چکیده
منابع مشابه
Analysis of tactile and visual confusion matrices.
Confusion matrices were compiled for uppercase letters and for braille characters presented to observers in two ways: as raised touch stimuli and as visual stimuli that had been optically filtered of their higher spatial frequencies. These and other existing matrices were subjected to a number of analyses, including the choice model and hierarchical clustering. The strong similarity of the visu...
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For many practical applications of keyword spotting, input signal is a spontaneous conversation while the acoustic model was trained with read speech because of data availability. Generally speaking, keyword spotting system will degrade significantly because of mismatch between acoustic model and spontaneous speech. To solve this problem, this paper presents a two-pass keyword spotting strategy...
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When assessing map accuracy, confusion matrices are frequently statistically compared using kappa. While kappa allows individual matrix categories to be analyzed with respect to either omission or commission error rates, kappa is not used to compare individual matrix categories with respect to both rates concurrently. When this concurrent comparison is desired, the ma trices are typically norma...
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Keyword Spotting (KWS) aims at detecting speech segments that contain a given query within large amounts of audio data. Typically, a speech recognizer is involved in a first indexing step. One of the challenges of KWS is how to handle recognition errors and out-of-vocabulary (OOV) terms. This work proposes the use of discriminative training to construct a phoneme confusion model, which expands ...
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ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Audio, Speech, and Language Processing
سال: 2016
ISSN: 2329-9290,2329-9304
DOI: 10.1109/taslp.2015.2512039